How to Become a Big Data Engineer: 8 Steps, Essential Skills, and Career Opportunities for 2025
Updated on Feb 03, 2025 | 10 min read | 10.9k views
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Updated on Feb 03, 2025 | 10 min read | 10.9k views
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Big data engineering is a rapidly growing field in India, fueled by the increasing volume of data generated across industries. With a CAGR of 36.7%, the sector is expected to reach USD 86.9 billion by 2027.
A big data engineer at a top tech company works on optimizing data pipelines to help reduce costs or improve customer experiences.
This blog explores how to become a data engineer, highlighting the steps, essential skills required, and career opportunities for big data engineers in 2025.
A data engineer is well-versed in some specific skill sets. This includes building a strong foundation in computer science, mastering key programming languages, and gaining hands-on experience with big data tools. Let’s first understand what the Big Data is:
Big data refers to datasets that are vast, complex, and grow at an exponential rate. These datasets often exceed the processing capabilities of traditional data management tools. Its defining characteristics are often summarized by the 5 Vs:
Also Read: Sources of Big Data: Where does it come from?
Ways to Become a Big Data Engineer in India
To start your journey as a Big Data Engineer, focus on building a strong foundation in key technical skills, programming, and data management principles. Here’s how you can begin:
A degree in computer science, IT, or mathematics forms the foundation for a big data engineering career. Certifications in tools like Hadoop or Spark, paired with hands-on projects, enhance expertise and employability.
As you establish a solid educational foundation, the next step is to focus on mastering the programming languages that will form the core of your big data engineering skills.
Programming languages form the core toolkit for big data engineers. Key languages to focus on:
In addition, learning SQL for querying databases and Bash for scripting is highly beneficial. The rise of cloud-based platforms such as AWS, Google Cloud, and Microsoft Azure also means learning cloud-specific tools like AWS Lambda and Google BigQuery will be increasingly important.
Mastering programming languages sets the foundation for working with big data, but to truly excel, it’s crucial to understand the tools and technologies that bring your code to life in the big data ecosystem.
Familiarity with big data tools and technologies is essential for building and managing large-scale data systems effectively. These tools play a critical role in handling diverse tasks, from storage to real-time processing.
Additionally, technologies like Delta Lake and Apache Iceberg are becoming vital for managing data lakes, offering capabilities like schema enforcement, ACID transactions, and optimized query performance.
These tools bridge the gap between big data storage and real-time processing, ensuring seamless data management and reliability in modern big data systems.
Also Read: Big Data and Hadoop Difference: Key Roles, Benefits, and How They Work Together
As you deepen your understanding of big data tools, it’s equally important to strengthen your knowledge in database management, ensuring you can effectively store, retrieve, and process large datasets across various systems.
Big data engineers must excel in managing both SQL and NoSQL databases to handle diverse data requirements:
Database security is essential, including encryption and GDPR compliance, as data volume and complexity increase.
Also Read: Top 10 Big Data Tools You Need to Know To Boost Your Data Skills in 2025
As you build your database management expertise, the next step is to focus on developing the essential data engineering skills that will allow you to design, implement, and optimize data systems effectively.
A successful big data engineer requires a blend of technical expertise and industry best practices to design and maintain efficient data systems. These skills enable the seamless processing, storage, and management of large datasets critical to modern business operations.
Also Read: Top 6 Skills Required to Become a Successful Data Engineer
To bridge the gap between building foundational skills and gaining practical experience, applying your knowledge through real-world projects is the perfect next step.
Practical experience is crucial to mastering big data engineering. While theoretical knowledge forms the foundation, applying that knowledge to solve real-world problems is what sets you apart.
Real-world projects not only help you understand how tools and technologies work in practice but also enhance your portfolio, showcasing your capabilities to potential employers.
Here’s how to gain hands-on expertise:
As you gain hands-on experience through real-world projects, earning certifications and staying updated will further solidify your expertise and keep you ahead in the fast-evolving field of big data.
Certifications not only validate your expertise but also help you overshadow competition. They demonstrate your commitment to learning and adapting to new technologies, making you more appealing to employers.
Consider pursuing certifications like:
Staying updated is equally important. Regularly explore webinars, take advanced courses, and attend industry conferences to learn about the latest tools and emerging trends in big data engineering. This ensures your skills remain relevant and aligned with industry demands.
As you gain new skills and certifications, connecting with industry professionals can further enhance your learning and open up exciting career opportunities.
A strong professional network can significantly accelerate your career in big data. It connects you with industry leaders, exposes you to the latest trends, and opens doors to collaborations and job opportunities. Networking also provides access to mentorship, helping you navigate challenges and refine your skills.
Here’s how you can expand your network:
Building connections with industry professionals can provide valuable insights into the skills and trends shaping the future of big data engineering. With the right network, you can sharpen the essential skills needed to thrive in the industry..
To excel as a big data engineer, develop the following skills:
Also Read: 8 Best Big Data Courses For Graduates To Elevate Your Career
As the demand for big data engineers continues to rise, it’s essential to not only master key skills but also understand the career opportunities that await in 2025.
The demand for big data engineers in India is booming. Industries like finance, healthcare, and e-commerce offer lucrative opportunities. Here are some of the top roles with average annual salary packages:
Role |
Average Annual Salary |
Big Data Engineer | INR 5L to INR 14L |
Data Architect | INR 20L to INR 34L |
Machine Learning Engineer | INR 6L to INR 18L |
Business Intelligence Analyst | INR 6L to INR 12L |
Data Warehouse Developer | INR 6L to INR 11L |
Source: Glassdoor
Also Read: Top 12 In-Demand Big Data Skills To Get ‘Big’ Data Jobs in 2025
The demand for big data engineers is making it an exciting career opportunity. Let’s see how upGrad can help you build the skills and confidence to thrive in the industry.
Becoming a data engineer begins with learning core skills like database management, and programming languages such as Python or SQL, tools like Apache Spark and cloud technologies, such as AWS or Azure. This role offers opportunities to work on complex data systems of businesses helping them to make key business decisions.
upGrad offers specialized programs to learn Big Data and Data Analysis, combining in-depth technical training, hands-on projects, and real-world case studies.
Here are some courses that can help you achieve your career goals:
Do you need help deciding which courses can help you excel in big data? Contact upGrad for personalized counseling and valuable insights. For more details, you can also visit your nearest upGrad offline center.
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