Data Engineering

Pranav Dobhal | Consultant | Calliope Data

What is Data Engineering?

You may be curious about a Career in Data Engineering. Internet is brimming with pages on How to get into Data Engineering, while one should first understand What is a Career in Data Engineering. Just like you would normally not trust a non Doctor with names of medicines, you should also not trust opinions about Data Engineering from non professionals.

Consultant Pranav Dobhal is an experienced professional with 4 years & 5 months in Data Engineering. According to Consultant Pranav Dobhal, Data Engineering is:

Data Engineering is the gathering, collecting and storing of data, conducting batch processing or real-time processing on it, and evaluating data solutions within organisations.

How Consultant Pranav Dobhal got into Data Engineering?

I did my Schooling from The Doon School, Dehradun after which I pursued an undergraduate degree in Information Systems from Brock University in Canada. I did a Masters degree in Information System Management from Carnegie Mellon University in Pittsburgh, USA.

Consultant Pranav Dobhal's Talk on Data Engineering

The Journey of Data Engineering What Is Data Engineering Data Engineering Data engineering is the discipline focused on designing, building, and maintaining systems that collect, store, process, and transform raw data into usable formats. It enables organizations to efficiently manage large volumes of data, ensuring accessibility, reliability, and quality for analytics, machine learning, and business intelligence applications. Data engineering plays a crucial role in the modern data-driven landscape by enabling organizations to harness the full potential of their data assets. For professionals in this field, it provides opportunities to solve complex problems, work with cutting-edge technologies, and drive business value through data. One major benefit is the ability to create scalable data pipelines that handle vast amounts of information efficiently. Another advantage is ensuring data quality and consistency, which is essential for accurate analytics and decision-making. Additionally, data engineering empowers organizations to innovate by making high-quality data readily available for advanced analytics, machine learning, and real-time applications, ultimately leading to better products, services, and customer experiences. A data engineer at a large e-commerce company might be responsible for building and maintaining a data pipeline that collects customer activity from the website, processes it in real time, and stores it in a central data warehouse. This system allows data analysts and data scientists to access up-to-date, reliable information about user behavior, sales trends, and inventory levels. By automating data collection and transformation, the data engineer ensures that business teams can quickly generate insights, optimize marketing campaigns, and improve customer recommendations. This real-world application of data engineering demonstrates how the discipline supports critical business functions and enables data-driven decision-making across the organization. Education Computer Science Computer Science is the systematic study of algorithms, data structures, computation, and the principles underlying software and hardware systems. It encompasses problem-solving, programming, and the theoretical foundations that drive technology. For Data Engineering, Computer Science provides the essential academic and professional framework needed to design, build, and optimize data systems. A strong grasp of Computer Science is indispensable for anyone pursuing a career in Data Engineering. This subject equips professionals with the ability to analyze complex problems, develop efficient algorithms, and understand the intricacies of data storage and retrieval. Mastery of core concepts such as data structures, algorithms, and computational complexity enables data engineers to create scalable and robust data pipelines. Furthermore, familiarity with computer architecture and operating systems enhances their ability to optimize performance and troubleshoot issues. Over the long term, this foundational knowledge not only improves technical proficiency but also fosters adaptability, allowing professionals to keep pace with evolving technologies and methodologies in the data landscape. Consider a data engineer tasked with optimizing a real-time data ingestion pipeline for a large e-commerce platform. Their understanding of Computer Science principles allows them to select the most appropriate data structures for buffering incoming data and to implement algorithms that efficiently process and transform this information. When faced with performance bottlenecks, their knowledge of computational complexity helps them identify and address inefficient code paths. Additionally, their familiarity with distributed systems and concurrency enables them to design solutions that scale horizontally, ensuring the pipeline remains reliable under heavy loads. In this scenario, the theoretical foundation provided by Computer Science directly informs practical decisions, resulting in a more efficient and resilient data engineering solution. Distributed Systems Distributed Systems refers to a collection of independent computers that appear to users as a single coherent system, working together to achieve a common goal. In Data Engineering, understanding distributed systems is essential, as modern data platforms rely on these principles for scalability, reliability, and efficient data processing across multiple machines. A solid grasp of distributed systems is indispensable for data engineers because most large-scale data infrastructure, such as Hadoop, Spark, and cloud-based data warehouses, are built on distributed architectures. Mastery of this subject enables professionals to design, implement, and maintain systems that can handle vast amounts of data with high availability and fault tolerance. Understanding concepts like data partitioning, replication, consistency, and distributed computation allows data engineers to optimize performance and ensure data integrity. Over the long term, this expertise not only enhances problem-solving abilities but also opens doors to advanced roles in data architecture, platform engineering, and technical leadership, making it a cornerstone of a successful data engineering career. Consider a data engineer working at a company that processes millions of user transactions daily. To ensure timely analytics and reporting, the engineer must design a data pipeline using Apache Spark, which distributes data processing tasks across a cluster of machines. Their understanding of distributed systems helps them configure the cluster for optimal resource utilization, manage data shuffling between nodes, and implement fault-tolerant mechanisms so that no data is lost if a machine fails. By applying theoretical knowledge of distributed coordination and consistency, the engineer ensures that the pipeline delivers accurate, up-to-date insights, even as data volumes grow and system demands increase. This practical application demonstrates how distributed systems expertise directly impacts the reliability and scalability of modern data solutions. Cloud Computing Cloud Computing is the on-demand delivery of computing resources, such as storage, processing power, and databases, over the internet. It enables organizations to access scalable and flexible infrastructure without owning physical hardware. For Data Engineering, cloud computing is a core competency, bridging academic theory and practical, industry-driven solutions. A strong grasp of cloud computing is essential for data engineers because it underpins modern data infrastructure and workflows. As organizations increasingly migrate to cloud platforms, data engineers must design, deploy, and manage scalable data pipelines that leverage cloud-native tools and services. Mastery of cloud computing concepts ensures professionals can efficiently handle large datasets, automate processes, and optimize costs. This foundational knowledge not only enhances immediate job performance but also positions data engineers for long-term career growth, as cloud technologies continue to evolve and dominate the data landscape. Understanding cloud computing opens doors to advanced roles and ensures adaptability in a rapidly changing technological environment. Consider a data engineer working for an e-commerce company that experiences fluctuating web traffic. By leveraging cloud computing, the engineer can design a data pipeline that automatically scales resources during peak shopping periods. Using cloud-based storage and processing services, they ingest, transform, and analyze customer data in real time, ensuring timely insights for business decisions. Their theoretical understanding of cloud computing enables them to select the right services, configure security settings, and optimize costs by shutting down unused resources. This practical application not only improves operational efficiency but also demonstrates the critical role of cloud computing knowledge in delivering robust, scalable data solutions in a dynamic business environment. Skills Programming Programming is the process of designing, writing, testing, and maintaining code that enables computers to perform specific tasks or solve problems. In data engineering, programming forms the backbone of building, automating, and optimizing data pipelines, ensuring data is efficiently collected, processed, and made accessible for analysis and business decision-making. Mastery of programming empowers data engineers to automate repetitive tasks, handle large-scale data transformations, and integrate diverse data sources seamlessly. Employers and clients highly value this skill because it leads to robust, scalable, and maintainable data systems that drive business insights and innovation. Programming proficiency allows professionals to adapt quickly to new technologies and evolving project requirements, making them indispensable team members. To cultivate this skill, aspiring data engineers should practice coding regularly, contribute to open-source projects, and stay updated with the latest programming languages and frameworks relevant to data engineering. Over time, consistent hands-on experience and a commitment to learning help transform programming from a basic competency into a powerful tool for career advancement. Imagine a data engineer at a retail company who discovers that daily sales data from multiple stores is arriving in inconsistent formats, causing delays in reporting and analysis. By leveraging programming skills, the engineer quickly writes a script to automatically standardize and validate incoming data, ensuring it conforms to the required schema before entering the central data warehouse. This solution not only resolves the immediate issue but also prevents similar problems in the future, enabling the business to access timely and accurate sales insights. The engineer’s ability to programmatically address data quality challenges demonstrates the critical role programming plays in maintaining reliable data infrastructure and supporting business objectives. Analytical Expertise Analytical Expertise is the ability to systematically collect, interpret, and evaluate complex data to identify patterns, solve problems, and make informed decisions. In data engineering, this skill enables professionals to design efficient data pipelines, optimize storage solutions, and ensure data quality, forming the backbone of reliable data-driven systems. Analytical Expertise directly enhances a data engineer’s ability to diagnose issues, optimize workflows, and anticipate potential bottlenecks in data systems. Employers and clients highly value this skill because it leads to more robust, scalable, and efficient data infrastructures, ultimately supporting better business decisions. Cultivating analytical expertise involves continuous learning, hands-on experience with diverse datasets, and staying updated with evolving analytical tools and methodologies. Engaging in challenging projects, seeking feedback, and collaborating with cross-functional teams further sharpens one’s analytical abilities. Over time, this skill becomes second nature, allowing data engineers to approach complex problems with confidence and deliver solutions that align with organizational goals. Imagine a data engineering professional tasked with integrating multiple data sources for a real-time analytics platform. Suddenly, the system begins to lag, and data inconsistencies appear. Relying on analytical expertise, the engineer systematically investigates the data flow, identifies a bottleneck caused by inefficient data transformation logic, and pinpoints a source of corrupted records. By redesigning the transformation process and implementing validation checks, the engineer restores system performance and data integrity. This scenario highlights how analytical expertise enables data engineers to dissect complex issues, devise effective solutions, and ensure the reliability of critical data systems, ultimately contributing to the success of the entire organization. Linus Operating System The Linus Operating System is a robust, open-source platform renowned for its stability, security, and flexibility. It serves as the backbone for many enterprise data systems, enabling seamless management of large-scale data pipelines, automation, and resource allocation. For data engineers, proficiency in Linus is indispensable for efficient infrastructure management. Mastering the Linus Operating System empowers data engineers to automate repetitive tasks, manage servers, and optimize data workflows with precision. Employers and clients highly value this expertise because it ensures reliable system performance, rapid troubleshooting, and cost-effective operations. Over time, professionals can cultivate this skill by exploring command-line utilities, scripting, and system administration tasks, gradually advancing to more complex configurations and optimizations. Continuous learning through real-world projects and staying updated with the latest Linus developments further enhances proficiency, making data engineers more adaptable and resourceful in dynamic environments. Imagine a data engineering professional tasked with maintaining a real-time analytics platform that suddenly experiences performance bottlenecks. By leveraging their expertise in the Linus Operating System, they quickly diagnose the issue using system monitoring tools, identify a misconfigured process, and implement a solution without downtime. Their ability to navigate the Linus environment, adjust permissions, and automate corrective actions not only resolves the crisis efficiently but also prevents future occurrences. This scenario highlights how deep knowledge of Linus enables data engineers to deliver resilient, high-performing solutions that are crucial for business continuity and client satisfaction. Server Administration Server Administration refers to the management, configuration, maintenance, and monitoring of servers to ensure their optimal performance, security, and reliability. In data engineering, this skill is crucial because it enables professionals to efficiently handle the infrastructure that supports data pipelines, storage solutions, and analytics platforms, ensuring seamless data operations. Mastering server administration directly enhances a data engineer’s ability to deploy, scale, and troubleshoot data systems, leading to more robust and reliable data workflows. Employers and clients highly value this skill because it minimizes downtime, ensures data security, and optimizes resource utilization, all of which are critical for business continuity and data-driven decision-making. Cultivating server administration expertise involves hands-on experience with various operating systems, cloud platforms, and automation tools, as well as staying updated with best practices in security and performance tuning. Over time, continuous learning and practical application help data engineers build confidence and proficiency, making them indispensable assets to any data-driven organization. Imagine a data engineering professional overseeing a large-scale ETL pipeline that suddenly experiences significant slowdowns. By leveraging server administration skills, the engineer quickly diagnoses the issue as a resource bottleneck on the underlying server infrastructure. Through efficient reconfiguration of server resources and optimization of system parameters, the engineer restores the pipeline’s performance, preventing data delivery delays and maintaining business operations. This scenario highlights how server administration expertise empowers data engineers to swiftly resolve critical issues, safeguard data integrity, and ensure the reliability of essential data services, ultimately contributing to the organization’s success and reputation. Database Management Database Management refers to the systematic process of storing, organizing, securing, and retrieving data using specialized software and methodologies to ensure data integrity, availability, and performance. In a Data Engineering professional’s toolkit, it serves as the backbone for handling large-scale datasets, enabling efficient data processing, analytics, and informed decision-making across organizations. Mastering Database Management directly enhances a data engineer’s ability to design robust data architectures, optimize query performance, and maintain data consistency across distributed systems. Employers and clients highly value this skill because it ensures that business-critical data remains accessible, reliable, and secure, supporting everything from real-time analytics to regulatory compliance. Cultivating expertise in this area involves hands-on experience with relational and non-relational databases, continuous learning about emerging technologies, and staying updated on best practices for data modeling, indexing, and backup strategies. Over time, practical exposure to diverse data environments and complex data challenges sharpens a data engineer’s proficiency, making them indispensable to any data-driven organization. Imagine a data engineer working for an e-commerce company facing slow website performance during peak shopping seasons. By leveraging their Database Management skills, the engineer identifies inefficient queries and poorly indexed tables as the root cause. They redesign the database schema, implement proper indexing, and optimize query execution plans, resulting in significantly faster data retrieval and a smoother user experience. This intervention not only resolves the immediate performance bottleneck but also ensures the system can scale to handle future growth. The engineer’s expertise in Database Management proves critical in maintaining business continuity, customer satisfaction, and the company’s competitive edge in a fast-paced digital marketplace. Positives High Demand High demand refers to the consistently strong need for skilled professionals in a particular field, driven by rapid technological advancements and the growing reliance on data-driven decision-making. In data engineering, this means organizations across industries are actively seeking experts to build, maintain, and optimize data systems, ensuring ongoing opportunities and career stability. The high demand for data engineers translates into a wealth of opportunities for career advancement, competitive salaries, and job security. Professionals in this field often find themselves at the forefront of innovation, collaborating with diverse teams and contributing to impactful projects. This constant need for their expertise fosters a sense of value and relevance, which can significantly boost job satisfaction. Data engineers experience professional growth as they tackle new challenges and adopt emerging technologies, knowing their skills are essential to organizational success. The daily recognition of their contributions and the assurance of future prospects make the profession both rewarding and motivating. Imagine a data engineer working at a leading healthcare technology company. As the organization expands its digital health services, the demand for robust data pipelines and real-time analytics grows rapidly. The data engineer is regularly approached by different departments seeking solutions to complex data challenges, highlighting their indispensable role. This constant engagement not only brings a sense of accomplishment but also opens doors to leadership opportunities and specialized projects. The professional feels empowered by the trust placed in their expertise and is motivated by the knowledge that their work directly impacts patient care and organizational growth. The high demand for their skills transforms daily tasks into meaningful contributions, fueling both personal and professional fulfillment. No Formal Education No Formal Education means entering a profession without a traditional academic degree or certification in the field. Instead, individuals rely on self-taught skills, online resources, hands-on projects, and practical experience. This approach fosters independence, adaptability, and creativity, allowing professionals to shape their learning journey and career path on their own terms. The absence of formal education requirements in data engineering opens doors for a diverse range of talent, welcoming those with unconventional backgrounds and unique perspectives. This inclusivity fuels innovation and encourages continuous learning, as professionals are motivated to stay current with rapidly evolving technologies. The freedom to learn at one’s own pace and focus on practical, real-world challenges leads to greater job satisfaction, as individuals see direct results from their efforts. Every day, data engineers experience the empowerment of solving complex problems using skills they have acquired independently, reinforcing their confidence and passion for the field. This dynamic environment not only accelerates career growth but also cultivates a strong sense of achievement and belonging. Imagine a data engineer who began their journey by experimenting with open-source data tools and contributing to online communities, rather than attending a formal university program. As they build data pipelines and optimize systems at work, they draw on knowledge gained from personal projects and collaborative forums. Their unconventional path allows them to approach problems creatively, unbound by traditional methods. When faced with a new challenge, they quickly adapt by researching and implementing the latest technologies, often introducing innovative solutions that inspire their team. The recognition and respect they earn from colleagues and leadership stem from their proven abilities, not academic credentials, making their daily work deeply fulfilling and validating the power of self-driven learning. Free Online Resources Free Online Resources are accessible digital materials such as tutorials, courses, documentation, forums, and open-source tools that require no financial investment. These resources empower aspiring and practicing data engineers to learn, solve problems, and stay updated with industry trends, regardless of their background or location. This accessibility fosters continuous growth and innovation within the profession. The abundance of free online resources is a transformative advantage for data engineers, making the field more inclusive and dynamic. With immediate access to high-quality learning materials and community support, professionals can quickly acquire new skills, troubleshoot issues, and experiment with emerging technologies. This constant flow of knowledge not only accelerates career growth but also enhances job satisfaction, as individuals feel empowered to overcome challenges and contribute meaningfully to their teams. The collaborative nature of these resources also fosters a sense of belonging and shared purpose, making daily work more engaging and less isolating. Ultimately, free online resources ensure that learning and professional development are ongoing, accessible, and tailored to each individual’s pace and interests. Imagine a data engineer tasked with implementing a new data pipeline using an unfamiliar technology. Instead of feeling overwhelmed, they turn to free online resources such as open-source documentation, community forums, and video tutorials. Within hours, they find detailed guides and real-world examples that clarify complex concepts. Engaging with an active online community, they receive prompt answers to specific questions and discover best practices shared by experts worldwide. This immediate support not only helps them complete their project successfully but also boosts their confidence and motivation. The experience demonstrates how free online resources transform challenges into opportunities for growth, making the journey in data engineering both fulfilling and accessible to all. Remote Work Remote work is a professional arrangement where individuals perform their job duties outside of a traditional office, often from home or any location with internet access. In data engineering, remote work enables professionals to leverage digital tools and cloud platforms, fostering flexibility, autonomy, and productivity while maintaining seamless collaboration with global teams. The ability to work remotely is a transformative benefit for data engineers, as it empowers them to design their ideal work environment and schedule. This flexibility leads to improved work-life balance, reducing stress and burnout. Data engineers can focus deeply on complex problem-solving without the distractions of a busy office, enhancing both creativity and efficiency. Remote work also opens doors to opportunities with organizations worldwide, allowing professionals to grow their careers without geographic limitations. Daily, data engineers experience greater autonomy, the freedom to innovate, and the satisfaction of contributing meaningfully to projects, all while enjoying the comforts of their chosen workspace. Imagine a data engineer based in a small town, collaborating with a leading tech company headquartered in another country. Each morning, they begin their day in a quiet home office, seamlessly accessing cloud-based data pipelines and participating in virtual meetings with colleagues across different time zones. Without the need for a lengthy commute, they dedicate more time to refining data models and exploring new technologies. The flexibility of remote work allows them to take breaks when needed, leading to sustained focus and higher-quality output. This arrangement not only supports their personal well-being but also enables them to contribute to innovative projects on a global scale, making their career in data engineering both fulfilling and impactful. Easy to Set-up and Practise "Easy to Set-up and Practise" means that the tools, platforms, and technologies required for data engineering are accessible, straightforward to install, and simple to experiment with. This allows professionals to quickly build, test, and refine data pipelines or solutions without facing steep technical barriers, fostering continuous learning and innovation. The ease of setting up and practising in data engineering is a game-changer for both newcomers and seasoned professionals. It eliminates the frustration of complicated installations and lengthy configurations, allowing individuals to focus on solving real-world data problems. This accessibility encourages experimentation, accelerates skill development, and empowers professionals to keep pace with rapidly evolving technologies. As a result, job satisfaction increases because engineers can see the immediate impact of their work, iterate quickly, and contribute meaningfully to their teams. The daily experience of being able to try out new tools or approaches without bureaucratic or technical delays makes the field dynamic and engaging, supporting both personal growth and organizational innovation. Imagine a data engineer who wants to optimize a company’s data pipeline for faster analytics. Thanks to cloud-based platforms and open-source tools, she can spin up a new environment in minutes, test different configurations, and visualize results almost instantly. This seamless process allows her to experiment with new frameworks, integrate cutting-edge technologies, and validate improvements without waiting for IT support or complex approvals. The ability to set up and practise so easily not only accelerates her learning but also gives her the confidence to innovate. She experiences the satisfaction of seeing her ideas come to life quickly, knowing that her contributions directly enhance the company’s data capabilities and decision-making. Challenges High Stress Job A high stress job in data engineering involves constant pressure to deliver reliable, scalable data solutions under tight deadlines, while managing complex systems and frequent changes in requirements. The role demands rapid problem-solving, continuous learning, and balancing multiple priorities, making it both intellectually stimulating and emotionally taxing. The high stress nature of data engineering can lead to burnout, reduced productivity, and errors if not managed properly. Daily work often involves urgent troubleshooting, late-night deployments, and responding to unexpected data issues, all while collaborating with cross-functional teams. This environment requires resilience, adaptability, and strong communication skills. Successful professionals develop coping mechanisms such as prioritizing tasks, setting realistic expectations with stakeholders, and leveraging automation to reduce repetitive work. They also focus on continuous learning to stay ahead of technological changes, and actively seek support from peers or mentors. By fostering a culture of open communication and self-care, data engineers can maintain their well-being and consistently deliver high-quality results despite the inherent pressures of the job. Consider a data engineer responsible for maintaining a real-time analytics platform during a major product launch. As user activity surges, unexpected data pipeline failures threaten to disrupt business insights. Instead of panicking, the engineer calmly assesses the situation, communicates transparently with stakeholders about the issue, and prioritizes critical fixes. By leveraging monitoring tools and automated alerts previously set up, the engineer quickly identifies the root cause and implements a solution, minimizing downtime. After the crisis, they conduct a post-mortem to improve system resilience and share lessons learned with the team. Through proactive preparation, clear communication, and a focus on continuous improvement, the engineer successfully manages the high stress environment and ensures the platform’s reliability. High Risk In Data Engineering, "High Risk" refers to the significant potential for costly errors, data breaches, or system failures due to the complexity and scale of data systems. This risk is demanding because even minor mistakes can lead to major business disruptions, regulatory penalties, or loss of stakeholder trust. The high-risk environment in Data Engineering means that professionals must constantly balance innovation with caution. Daily work involves making decisions that could have far-reaching consequences, such as deploying new pipelines or handling sensitive data. This pressure can lead to stress and requires a high degree of resilience, as mistakes are often visible and impactful. Successful data engineers manage this risk by rigorously testing their solutions, implementing robust monitoring, and fostering a culture of peer review and knowledge sharing. They also stay current with industry best practices and compliance requirements, ensuring that their work not only meets technical standards but also aligns with organizational and legal expectations. By embracing continuous learning and proactive communication, they turn risk into an opportunity for growth and improvement. Consider a data engineer tasked with migrating a company’s critical data infrastructure to a new cloud platform. The project carries high risk, as any data loss or downtime could disrupt business operations and damage client relationships. The engineer approaches the challenge by meticulously planning the migration, setting up comprehensive backup systems, and conducting multiple dry runs in a test environment. Throughout the process, they communicate transparently with stakeholders, ensuring everyone is aware of potential risks and mitigation steps. When a minor issue arises during the final migration, the engineer quickly identifies and resolves it thanks to the robust monitoring and contingency plans in place. The successful migration not only avoids disaster but also builds trust in the engineer’s ability to manage high-risk situations. Ever-Evolving Landscape The "Ever-Evolving Landscape" in Data Engineering refers to the relentless pace of change in technologies, tools, frameworks, and best practices. Professionals must constantly adapt to new data storage solutions, processing paradigms, and integration methods, making it demanding to maintain expertise, ensure system compatibility, and deliver reliable, future-proof data solutions. This constant evolution impacts daily work by requiring data engineers to frequently learn new skills, update existing systems, and evaluate emerging technologies. The pressure to stay current can be overwhelming, demanding resilience and adaptability. Successful professionals manage this by cultivating a mindset of continuous learning, actively seeking out educational resources, and participating in professional communities. They prioritize foundational concepts over fleeting trends, allowing them to quickly adapt when new tools emerge. By fostering strong collaboration with peers and maintaining a flexible approach to problem-solving, they turn the challenge of rapid change into an opportunity for growth and innovation, rather than a source of stress or stagnation. Consider a data engineer working at a fintech company who faces the introduction of a new cloud-based data warehousing solution. Rather than resisting the shift, this professional proactively attends vendor webinars, experiments with pilot projects, and collaborates with colleagues to migrate legacy pipelines. By leveraging online courses and engaging in open-source communities, they quickly gain proficiency in the new platform. Their willingness to embrace change not only ensures a smooth transition for their team but also positions them as a valuable resource within the organization. This adaptability enables the company to harness the latest technology, improve data processing efficiency, and maintain a competitive edge in a rapidly shifting industry. A Day Of Managing Data The hum of servers and the quiet click of keyboards set the rhythm for a data engineer’s day—a blend of deep technical focus, creative problem-solving, and seamless collaboration. In a world where terabytes of information flow ceaselessly, data engineers are the architects and custodians, ensuring that raw data transforms into actionable insights. Their workday is a dynamic journey, marked by early-morning strategizing, high-stakes troubleshooting, and the constant balancing act between innovation and reliability. Each hour brings new challenges and opportunities, making every day both demanding and deeply rewarding. As the sun rises, a data engineer’s first priority is to review the overnight data flows and system health dashboards. This quiet window is dedicated to scanning logs for anomalies, verifying that scheduled ETL jobs have run smoothly, and ensuring that data pipelines are delivering fresh, accurate information to downstream teams. With a mug of coffee in hand, the engineer might tweak configurations or rerun failed processes, setting the stage for a productive day ahead. Mid-morning brings the heart of the action: designing, coding, and optimizing data pipelines. This is when the engineer dives into writing new scripts, refactoring existing code, or integrating new data sources. The work is intense and immersive, often requiring deep concentration to solve complex data transformation challenges or to debug elusive errors. Collaboration with data scientists or analysts may occur here, as the engineer ensures that the infrastructure supports evolving business needs and analytical models. Afternoons are often punctuated by team stand-ups, project meetings, and cross-functional discussions. The data engineer shares progress updates, discusses blockers, and aligns with product managers, analysts, and fellow engineers on upcoming priorities. After meetings, the focus shifts to executing on project tasks—deploying new features, updating documentation, or conducting code reviews to maintain high standards of quality and security across the data ecosystem. As the day winds down, the engineer turns attention to documenting changes, reviewing system performance metrics, and responding to outstanding support tickets. This is also a time for researching new tools or techniques that could improve future workflows. Before logging off, the engineer reviews the next day’s agenda, sets priorities, and ensures that all critical processes are queued up for the overnight cycle, closing the loop on another fast-paced, data-driven day.

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How to get into

Data Engineering?

If you are want to get into Data Engineering, start by investing in a Career Plan.

The 14 hour process, guided by a LifePage Career Advisor, will help you introspect and check whether your interest in Data Engineering is merely an infatuation or is it truly something you wish to do for the rest of your life.

Next, your Career Advisor will help you document how you can get into Data Engineering, what education and skills you need to succeed in Data Engineering, and what positives and challenges you will face in Data Engineering.

Finally, you will get a Career Plan stating which Courses, Certifications, Trainings and other Items you need to do in the next 7 years to become world’s best in Data Engineering.

LifePage Career Plan

14 hour personalized guidance program

Your LifePage Career Advisor facilitates your guided introspection so that you systematically explore various Career options to arrive at a well thought out Career choice.

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LifePage Plan will not stop at saying "to become an Architect study Architecture". It will guide you on which Certifications, Trainings and Other items you need to do along with your Architecture education to become the world's best Architect.

Links for this Talk

Consultant Pranav Dobhal's LifePage:

[LifePage]
https://www.lifepage.in/page/pranavdobhal

LifePage Career Talk on Data Engineering

[Career]
https://www.lifepage.in/careers/data-engineering

[Full Talk]
https://lifepage.app.link/20171103-0001

[Trailer]
https://www.youtube.com/watch?v=7JEJlVNLnuE

(Data Engineering, Pranav Dobhal, Calliope Data, programming, big data, computing)

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Cyber Security

Nitin Pandey
Chairman | National Information Security Counsel

[ 11 years Experience ]

Cyber security or information technology security are the techniques of protecting computers, networks, programs and data from unauthorized access or attacks that are aimed for exploitation.

"I did my BCA and MCA from Lucknow University and pursuing my Ph D from SGT, Gurgaon. I have been conducting workshops related to cyber security since 2007. I was the head of DEFCON & OWASP, Luchnow for four years. I am working as the Chairman of National Information Security Council (NISC) since 2017."

PHP Development

Jitendra Kumar
PHP Developer | M and P Technologies

[ 2 years Experience ]

PHP is a general-purpose scripting language that is especially suited to server-side web development, in which case PHP generally runs on a web server. Any PHP code in a requested file is executed by the PHP runtime, usually to create dynamic web page content or dynamic images used on websites or elsewhere.

"After completing my graduation, I did my MCA from DBIT, Dehrdaun. Currently, I am working as a PHP Developer at M and P Technologies, Dehradun."

Mobile App Development

Suyash Joshi
Senior Mobile Software Engineer | Oracle

[ 8 years Experience ]

Mobile application development is the act or process by which a mobile app is developed for mobile devices, such as personal digital assistants, enterprise digital assistants or mobile phones. These applications can be pre-installed on phones during manufacturing platforms, or delivered as web applications using server-side or client-side processing (e.g., JavaScript) to provide an "application-like" experience within a Web browser. Application software developers also must consider a long array of screen sizes, hardware specifications, and configurations because of intense competition in mobile software and changes within each of the platforms.

"I have a Bachelors in Computer Science from University of Michigan, USA. I am currently pursuing a Masters degree from Georgia Tech. Since 2010, I have been working at Oracle, San Francisco as a Senior Mobile Software Engineer."

Computer Coding

Dipankar Tripathi
Head | Airvana Networks

[ 9 years & 5 months Experience ]

Computer coding is making computers do what one wants them to do. For making a computer do something we need to write something which the computer is able to understand and then perform that by itself.

"I did my Graduation from DAV and Masters in Computers from IP University. In 2009 I shifted to Bangalore and that is when I got a break in Computer coding. I started working for a company called Airvana Networks."

Machine Learning

Pranav Dobhal
Consultant | Calliope Data

[ 4 years & 5 months Experience ]

Data Engineering is the gathering, collecting and storing of data, conducting batch processing or real-time processing on it, and evaluating data solutions within organisations.

"I did Schooling from The Doon School, Dehradun after which I pursued an Undergraduate Degree in Information Systems from Brock University in Canada. I did a Masters degree in Information System Management from Carnegie Mellon University in Pittsburgh, USA."

Software Engineering

Rohit Verma
Senior Software Developer | ST Microelectronics

[ 6 years & 9 months Experience ]

Software engineering is a detailed study of engineering to the design, development and maintenance of software.

"I did my Bachelors in Computer Application from Kurukshetra University and Masters in Computer Application from YMCA, Faridabad. After completing studies in 2012 I joined ST Microelectronics as a Software Developer. I am Senior Software Developer in ST Microelectronics."

Website Design & Development

Kunal
Director Technology | Orbosys Co-operation

[ 7 years & 9 months Experience ]

Website design encompasses many different skills and disciplines in the production and maintenance of websites. The different areas of web design include web graphic design; interface design; authoring, including standardised code and proprietary software; user experience design; and search engine optimization.

"I did B Tech in Information Technology from NSIT, Kanpur. During college, I started a website design company by the name Biztech Work Solutions, which I had to close because of the limited market opportunities in Kanpur. I did a course in Linux from IIT, Kanpur. I then started a company in Dehradun with my cousin brother in 2012 by the name Orbosys Co-operation. I am Director-Technolgy at Orbosys."

Artificial Intelligence

Dr Kiran Kumar Ravulakollu
Assistant Dean - Research | UPES

[ 7 years & 1 month Experience ]

In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals.

"After graduating in B Tech from JNTU, Hyderabad, I went on to do M Sc in Artificial Intelligence from City University, London. I also did a Ph D in Neurorobotics from University of Sunderland, UK. I came to India and started teaching at Sharda University as an Assistant Professor. I switched to UPES and went on to become Assistant Dean - Research."

Software Development

Amit Naithani
Module Lead | MothersonSumi Infotech & Design Limited

[ 9 years & 2 months Experience ]

Software development is the process of conceiving, specifying, designing, programming, documenting, testing, and bug fixing involved in creating and maintaining applications, frameworks, or other software components.

"After completing my Schooling from Dehradun, I did B Tech in Computer Science Engineering. I have worked with Infosys, KPIT and Infotech. I have also worked on Oracle, JD Edwards and ERP system. I am working as a Module Leader at Motherson Sumi, Delhi."

User Interface Development

Prachi Pant
UI Developer | Snapdeal

[ 4 years Experience ]

User Interface Development combines programming, psychology and creative design to craft intuitive controls for software and hardware. The UI developer's mission is to create an interface that behaves as users would it expect it to, facilitating a seamless and efficient user experience.

"I did my B Tech (Information Technology) from Roorkee Engineering College after which I joined a Delhi-based startup called Cloudchowk Solutions Pvt Ltd. Later, I moved to Snapdeal. At both places I worked in the domain of user interface development."

Computer Engineering

Daniel Cohen
Computer Engineer | Facultad de Ciencias Exactas y Tecnologia, UNT

[ 30 years Experience ]

Computer engineering has an integral vision of the computer, from the layers related to the user, the apps, to the layers related to the computer, the hardware and even the ones related to the intercommunication between the computers, the internet. So computer engineering is just a career in engineering that achieves an integration of all the knowledge that is in computers so they are able to have a very widespread application. Including all the achievements that have been seen lately as cell phones, all machines applied to medicine and artificial intelligence. All of them are areas of application of computer engineering.

"I graduated first as an electronic engineer, because at that time when I studied, computer engineering did not exist in my country as a career. Soon after I graduated as an electronic engineer I won a scholarship to study in Israel where I did a master's degree in computer engineering at the Technological Institute of Israel called Technion. Since I returned I have been very active in my professional life, but I have never stopped being a teacher at UNT, at the beginen only part time because the rest of the time I used it in my own professional career."

Teaching Computer Science

Ashish Saxena
Assistant Professor | DIT University

[ 15 years & 1 month Experience ]

Computer science and engineering (CSE) is an academic program that integrates the fields of computer engineering and computer science. It is a sub-field of electronics engineering. It covers the digital aspects of electronics engineering, specializing in hardware-systems areas like computer architecture, processor design, high-performance computing, parallel processing, computer networks and embedded systems.

"After completing B Sc, I did MCA from H N B Garhwal University and M Tech from UTU, Dehradun. I have taught in a school for 2 years and at Amrapali Institute, Haldwani for 3 years. I have been teaching at DIT University since 2008. I am Assistant Professor at DIT University."

Game Development

Pankaj Badoni
Assistant Professor | Graphics & Gaming, UPES

[ 7 years & 2 months Experience ]

Game development is the process of creating a video game. The effort is undertaken by a game developer, who may range from a single person to an international team dispersed across the globe. Game programming requires substantial skill in software engineering as well as specialization in one or more of the following areas, which overlap heavily to create a game: simulation, computer graphics, artificial intelligence, physics, audio programming, and input.

"After doing B Tech in Computer Science & Engineering, I went on to do masters in IT with a specialisation in Human Computer Interaction. I worked as a Developer at Headstrong India for few years before switching to academia. I am an Assistant Professor at UPES and manage Graphics and Gaming branch there."

Software Engineering & Development

Harsh
Software Engineer and Developement | Hike Messenger

[ 3 years & 1 month Experience ]

In software engineering, a software development process is the process of dividing software development work into distinct phases to improve design, product management, and project management. It is also known as a software development life cycle. Software engineering is an engineering branch associated with development of software product using well-defined scientific principles, methods and procedures. The outcome of software engineering is an efficient and reliable software product.

"After completing B Tech (Hons) in Computer Science & Engineering from Dehradun Institute of Technology, I started working as a Software Engineer at Hike Messenger. My role as a software engineer was to explore and dive into various aspects of big-data technologies and machine learning, fixing regular issues/bug, developing content visualization console (WT-Forms, Python, Flask, HTML, CSS, JS) etc. I have also worked as a Software Developer Research Intern at Indian Institute of Remote Sensing (IIRS), Indian Space Research Organization (ISRO)."

Server Administration

Abhishek Mishra
Specialist | HCL

[ 1 year & 10 months Experience ]

A server administrator, or admin has the overall control of a server. This is usually in the context of a business organization, where a server administrator oversees the performance and condition of multiple servers in the business organization, or it can be in the context of a single person running a game server.

"After doing my schooling, I did my B Sc and MCA from Kanpur University. After that I started working as an IT Administrator in Amway and then I worked for various companies like Dell and Capgemini. I am working as a Specialist with HCL since 2016."

System Software Development

Anand Krishnaswamy
System Architect | IBM

[ 8 years Experience ]

In software engineering, a software development process is the process of dividing software development work into distinct phases to improve design, product management, and project management. It is also known as a software development life cycle. Software engineering is an engineering branch associated with development of software product using well-defined scientific principles, methods and procedures. The outcome of software engineering is an efficient and reliable software product.

"For 14+ years in the software industry, I played my role in teams that created business value in writing software, software consulting, inventing & creating patents & insightful articles. It drives my interest in data science & data analytics. Clean & pertinent design is the reward I work for. As a software consultant, I've focused on delivering exactly what the business needs. I've helped clients sift through & identify what they really want vs what they think they want & then led teams to deliver that. Tough conversations, but many a client has appreciated the effort put into gleaning that. Today, I focus this drive to create relevant & vital value in the effort to educate underprivileged children so that they are not left handicapped in competing in the world at large."

Code Analysis

Neeti
Analyst | HCL Technologies

[ 3 years Experience ]

Code Analysis is the automated testing of source code for the purpose of debugging a computer program or application before it is distributed or sold.

"I did my schooling from St Thomas College, Dehradun and B Tech from Graphic Era University, Dehradun. After completing my education, I started working at HCL, Noida as an Analyst."

Cloud Software Engineering

Shrinath K T
Cloud Development Manager | Revevol Technology

[ 5 years & 2 months Experience ]

Cloud computing or Cloud Software Engineering is an information technology (IT) paradigm that enables ubiquitous access to shared pools of configurable system resources and higher-level services that can be rapidly provisioned with minimal management effort, often over the Internet. Cloud computing relies on sharing of resources to achieve coherence and economies of scale, similar to a public utility.

"After completing my schooling from Cinmaya Vidyalaya Coimbatore, I did my BE in Computer Science from CIET, Coimbatore. I worked as a Tech Support Executive for CSS Corp, Chennai and after that I worked for Tata Communications, Chennai. I am working as a Cloud Development Manager with Revevol Technology, Delhi."

Database Administration

Varun Yadav
Sr Oracle Database Administrator | Motherson Sumi Infotech & Designs Ltd

[ 8 years & 3 months Experience ]

Database administration refers to the whole set of activities performed by a database administrator to ensure that a database is always available as needed. Other closely related tasks and roles are database security, database monitoring and troubleshooting, and planning for future growth. Database administration is an important function in any organization that is dependent on one or more databases. Database administrators (DBAs) use specialized software to store and organize data. The role may include capacity planning, installation, configuration, database design, migration, performance monitoring, security, troubleshooting, as well as backup and data recovery.

"After doing my schooling from Chandigarh, I did my BE & ME from Punjab Engineering College, PEC University of Technology, Chandigarh. Thereafter, I worked as a Sr. Oracle Data Base Administrator with different companies like Path InfoTech Ltd, Wipro Technologies and others on different projects like Financial, Banking Domain and Telecommunication. Later, I joined Motherson Sumi Infotech and Design, Noida as Sr. oracle Data Administrator."

Software Engineering

Manish Kumar
Senior Consultant | HCL Technologies

[ 12 years & 9 months Experience ]

Software engineering is a detailed study of engineering to the design, development and maintenance of software.

"I did B Tech in Electronics & Communication from Birla Institute of Technology, Ranchi. I worked at Computer Science Corporation for some time as a consultant before switching to HCL Technologies in 2013. I am a Senior Consultant at HCL Technologies."

Software Development

Raj Kumar Saini
Mentor & Central Head, Dehradun | Coding Blocks

[ 3 years & 5 months Experience ]

Software development is the process of conceiving, specifying, designing, programming, documenting, testing, and bug fixing involved in creating and maintaining applications, frameworks, or other software components.

"I did my graduation in B Tech in Computer Science from Delhi Technological University. I got a campus placement as Software Developer at Amazon. I worked there for some time before switching to D.E.Shaw. I have also worked at Adobe, Right Relevance and Caroobi. I am Mentor & Central Head at Coding Blocks, Dehradun."

UX/UI Designing

Naina Jain
UX Designer | ImaginXP

[ 6 years & 2 months Experience ]

UX stands for user experience. A users experience of the app is determined by how they interact with it. User experience is determined by how easy or difficult it is to interact with the user interface elements that the UI designers have created. The UI in UI design stands for user interface.The user interface is the graphical layout of an application. It consists of the buttons users click on, the text they read, the images, sliders, text entry fields, and all the rest of the items the user interacts with.

"While I was in college and studying communication design, I started working as a designer. My first project was for a restaurant based out of Gurgaon. I have had done various projects such as with TedX, Govt of Uttarakhand as well as Karnataka and various other projects. I am also the co-founder of a design company known as NUTS India as well as I am working for ImaginXP which is into education sector for designing. Therefore, I am posted at DIT University, Dehradun and teaching designing there as well as running own design studio."

DevOps

Monit Kapoor
Associate Professor & HoD Cybernetics | School of Computer Science, UPES

[ 19 years & 2 months Experience ]

DevOps is a software development methodology that combines software development with information technology operations. The goal of DevOps is to shorten the systems development life cycle while delivering features, fixes, and updates frequently in close alignment with business objectives.

"After completing my bachelors in engineering in electrical, I went on to do a masters in Computer Science & Engineering. Post that, I started working at Green Hills Engineering College as an HOD of IT. I then switched to Maharishi Markandeshwar University, Solan as an HoD of CSE & Computer Applications. I finally moved to UPES, Dehradun as an Assistant Professor in 2011. I did a Ph D in Mobile Ad Hoc Networks along with professorship. I am an Associate Professor and HoD Cybernetics at UPES."

Full Stack Development

Sagar Gurung
Full Stack Developer | Ifadvertisings

[ 7 years & 1 month Experience ]

A full stack developer is an engineer who can handle all the work of databases, servers, systems engineering, and clients. Depending on the project, what customers need may be a mobile stack, a Web stack, or a native application stack.

"After completing B Tech in EEE, I started my own company by the name Web Plan Solution Pvt Ltd. After running it for 2 years, I decided to shut it down and did certifications in Java, PHP, .Net & Robotics. I then worked with Mymind Infotech as a Senior Developer for 2 years. In 2018, one of my friends and me came together to work on an advertising mobile application called Ifadvertisings. I developed the application single handedly. I am Co-founder & Full Stack Developer at Ifadvertisings."

Application Development

Amruta N
Senior Consultant | OpenText

[ 4 years Experience ]

Application development is the process of creating a computer program or a set of programs to perform the different tasks that a business requires. From calculating monthly expenses to scheduling sales reports, applications help businesses automate processes and increase efficiency.

"After completing my BCA & MCA from R V college, Bangalore in 2014, I began working as an Associate Software Consultant at Muraai Information Technology. I moved to Adnate IT Solutions as a Consultant in 2015. In 2017 I joined OpenText, where I am working as a Senior Consultant."

Software Development

Gargi Gautam
IT Analyst | Tata Consultancy Services

[ 3 years & 9 months Experience ]

Software Development is a process followed for a software project, within a software organization. It consists of a detailed plan describing how to develop, maintain, replace and alter or enhance specific software. The life cycle defines a methodology for improving the quality of software and the overall development process

"After completing my graduation from Uttar Pradesh Technical University in Computer Science (GNIT) in 2012, I started working with Sears IT & Management Services private limited where I worked till 2015 while I was a System Engineer. After that I have joined Tata Consultancy Services where my designation is IT Analyst. Meanwhile in 2017 I had completed my Post Graduation Diploma in Management in Operations Management from All India Management Association."

Teaching & Research in Data Science

Dr Kingshuk Srivastava
Assistant Professor | UPES

[ 9 years Experience ]

Teaching and Research in Data science of three words teaching, research and data science so first of all what is teaching so teaching is the art and science of helping others to grow in their knowledge and understanding. It is holding the hand of a young one and saying it's going to be OK. Teaching is being careful that you acknowledge every student ever. On the other hand research is a careful and detailed study into a specific problem, concern, or issue using the scientific method. It's the adult form of the science fair projects back in elementary school, where you try and learn something by performing an experiment. Data science is a multidisciplinary blend of data inference, algorithmm development, and technology in order to solve analytically complex problems. Data Science can be applied to a data set with one thousand lines, there is no problem with this.

"After completing my B Sc in Physics & M Sc in Electronics from Lalit Narayan Mithila University, I did M Tech in Information Technology & Ph D in Computer Science Engineering from University of Petroleum & Energy Studies (UPES). I am an Assistant Professor Selection Grade at University of Petroleum & Energy Studies, Dehradun."

Software Engineering

Vikas Nokhwal
Founder & Senior Software Developer | Nokhwal Technologies

[ 5 years & 6 months Experience ]

Software engineering is a detailed study of engineering to the design, development and maintenance of software.

"I did B.Tech in Computer Science from Om group of Institutions, Hisar. I started working in SSN Ventures as Software Developer. After working for four years with the company, I started my own firm, Nokhwal Technologies in 2017. I am Senior Software Developer at Nokhwal Technologies."

Nature Inspired Computing

Deepshikha Bhargava
Professor & HoD | UPES

[ 21 years & 2 months Experience ]

Nature-inspired computing is a very new discipline that strives to develop new computing techniques through observing how naturally occurring phenomena behave to solve complex problems in various environmental situations. This has produced groundbreaking research that has created new branches, like neural networks, swarm intelligence, evolutionary computation and artificial immune systems.

"After graduating from University of Rajasthan, I went on to do M Sc, MCA & M Tech (CS). I also hold a Ph D (Computer Science) with specialisation in Artificial Intelligence. I have been working in this area for over 20 years. I am Professor & HoD - Visualisation Dept at UPES."

Cloud Computing

Rajeev Tiwari
Associate Professor | UPES

[ 13 years & 2 months Experience ]

Cloud computing is shared pools of configurable computer system resources and higher-level services that can be rapidly provisioned with minimal management effort, often over the Internet. Cloud computing relies on sharing of resources to achieve coherence and economies of scale, similar to a public utility.

"I did bachelors and masters in Computer Science. Post that, I pursued a Ph D in Computer Science. I am aslo AWS certified. I have served as an Assistant Professor at Maharishi Markandeshwar University, Mullana & at HEC, Jagadhri. I am an Associate Professor at University of Petroleum & Energy Studies, Dehradun."

Information Technology

Manish Prateek
Dean & Professor | UPES

[ 22 years Experience ]

Information technology is the use of computers to store, retrieve, transmit, and manipulate data, or information, often in the context of a business or other enterprise.

"After completing my B Tech & M Tech in Computer Science Engineering from KURSK State Technical University, Russia, I did Ph D in Robotics. I joined Tirupati Enterprises as IT Manager in 2001. After working there for 4 years, I moved to academia with GRIET, Hyderabad. In 2010, I joined UPES. I am a Professor & Dean at UPES."

Software Engineering

Devendra Dutt Bijalwan
Senior Analyst | Accenture

[ 9 years & 3 months Experience ]

Software Engineering is the process of analyzing user needs and designing, constructing, and testing end user applications that will satisfy these needs through the use of software programming languages. It is the application of engineering principles to software development. In contrast to simple programming, software engineering is used for larger and more complex software systems, which are used as critical systems for businesses and organizations.

"After completing my MCA, I started my Career as a Software Engineer by joining Avalon Information Systems. There, I worked with many NGOs. After spending 3 years with Avalon, I joined FIS Global Business Solutions in 2015 and worked on a lot of banking projects with them. After another 3 years, I joined Accenture as Senior Analyst in 2019."

Teaching Computer Science

Rajan Gupta
Assistant Professor | University of Delhi

[ 6 years & 2 months Experience ]

Computer Science is an academic program that integrates the fields of computer engineering and computer science. It covers the digital aspects of electronics engineering, specializing in hardware-system areas like computer architecture, processor design, high-performance computing, parallel processing, computer networks and software aspects.

"I am a Research & Data Analytics professional, learning new ways to deal with various business and research problems through technological and analytical tools. With the help of past experiences and academic exposure, following are the highlights of current capabilities. I have a substantial experience of working on research & analytics projects in the area of Information Systems, E-Governance and Public Schemes Assessment. I have working knowledge of application of various data science concepts through statistical techniques, operation research & optimization, data mining and machine learning across multiple industries (healthcare, retail, education, etc.) and domains. I have hands-on experience of using various analytical & development tools like SPSS, R, Tableau/MS Power BI and MATLAB and exposure of training and teaching in specialized areas of IT & Analytics. I am UGC NET-JRF Qualified and also possess management consulting certification from Government of India. I am one of the few Analytics professional in India to have CAP (INFORMS) and GStat (ASA) certification & accreditation, respectively and also serving as the Brand Ambassador of CAP in Asia Region for INFORMS. I am efficient in report preparation and article writing. I can prepare research proposals, research frameworks, data source identification, data collection framework and data preparations. I have experience of handling teams up to 50 people for project execution."

DevOps

Sricharan Vadapalli
Practice Head | Pyramid Solutions

[ 7 years & 7 months Experience ]

DevOps is the combination of cultural philosophies, practices, and tools that increases an organization's ability to deliver applications and services at high velocity: evolving and improving products at a faster pace than organizations using traditional software development and infrastructure management processes.

"I did BTech in Mechanical Engineering from Nagarjuna University and M Tech in Mechanical Engineering from IIT Delhi. After that I joined TCS as product manager and worked there for 8 years. I have also worked with Infosys, CSC, Virtusa Polaris, Kogentix, Pyramid Consulting Inc and CTO for a startup, I was author at Packt and written books on Devops, Bigdata and Reality of Relations. I am currently working with Sunera Tech as VP and Practice Head of Data Monetization ( Analytics, Machine Learning, Devops on Cloud)."

Software Engineering

Amit Ved
Application Development Manager | ST Microelectronics

[ 15 years & 7 months Experience ]

Software engineering is the application of engineering to the development of software in a systematic method.

"I did B Sc & M Sc in Statistics from Kanpur University. I then did an MCA from UPTU and started working at India Worldwide Software System as Software Tester. In 2004 I joined ST Microelectronics as Software Support Professional. I am now an Application Development Manager at ST Microelectronics."

Technology Sales

Ankkit
Sales & Strategic Alliance Manager | Tejas Networks

[ 10 years & 1 month Experience ]

Technology sales professionals sell advanced devices such as computers to individuals and businesses. While many jobs exist in retail stores, some technology sales professionals travel to offices, workshops, and sales events such as conventions and expos.

"After completing BE & MBA, I started with Bharti Airtel and continued working with various MNC's. Post that, I joined Tejas Networks as the Sales & Strategic Alliance Manager."

DevOps & Unix Administration

Rahul Parsai
Team Lead | STMicroelectronics

[ 10 years & 1 month Experience ]

DevOps is a set of software development practices that combines software development and information technology operations to shorten the systems development life cycle while delivering features, fixes, and updates frequently in close alignment with business objectives.

"After completing my B Tech from NIT Bhopal, I worked at HCL as Engineer Trainee. I then worked at Supra Group of Industries as a Software Engineer and then at Steria Consulting Pvt Ltd as Senior Software Engineer. I am working at STMicroelectronics as Team Lead."

Emerging Technologies

Munish Dhiman
CEO | Gesture Research International Ltd

[ 8 years & 6 months Experience ]

Technology entrepreneurship is an investment in a project that assembles and deploys specialized individuals and heterogeneous assets that are intricately related to advances in scientific and technological knowledge for the purpose of creating and capturing value for a firm.

"After completing my education, I worked as an Analyst at THEIKOS INDIA Pvt Ltd for 6 months. Later I worked as a Project Manager at V- Microsoft Crop United States. In 2010, I worked as Strategic Advisor and Consultant at Multiverse. In 2012, I started my own venture called Gesture Research International Ltd and I am also the Managing Partner with CivilCops Dubai, United Arab Emirates."