What is Data Engineering?: Course Fees 2025, Subjects, Top Colleges, Admissions

Data Engineering revolves around the creation and management of large-scale data pipelines and models used for the collection, storage, and conversion of raw data into valuable insights that assist data scientists and analysts to derive valuable and meaningful insights. Data Engineering courses are very important for business scalability and innovation.

Well, yes. A strong hold over programming languages is very important for data engineers because they are involved in building data pipelines, working with complex datasets, and data cleaning, processing and automation tasks. None of this is possible without mastery in programming languages like Java, Python, Scala, etc., which are important for strategic and scalable business solutions.

Data Engineering is not only coding but rather a whole lot of other skills are required to excel in the field. No doubt programming language proficiency in Python and SQL are the backbone for building robust data pipelines and infrastructure, but you should also know what data warehousing is, how database systems function and big data technologies combined with critical thinking aptitude.

You can find the list of some important technical and soft skills needed for career success after learning Data Engineering here:

Data Engineering courses are mostly offered in the online mode through e-learning platforms or universities. A few online courses may require general aptitude tests and a background in CS, IT, or Science/Mathematics, but there are no specific entrance exams as such for online platforms.

Having said that, when it comes to the Data Engineering courses online offered by universities, SRM Institute of Science and Technology offers an M.Tech in Data Engineering course for which you will to clear the SRMJEEE (PG) entrance exam.

Well, you can do well as a data engineer with basic mathematical knowledge like linear algebra, arithmetic, and a strong understanding of statistics and set theory. Data Engineering is more about data infrastructure and software development, along with database management and data pipelines rather than mathematical computations. Learn math and statistics in the practical sense of data pipeline design and processing rather than core theoretical subjects.

Yes, of course, you can opt for free Data Engineering courses, which can be of a few hours duration or stretch up to a few weeks/months. Some of the best Data Engineering courses online free are given here:

• Spark, Hadoop, and Snowflake for Data Engineering by Coursera
• IBM - Introduction to Data Engineering by Coursera
• Advanced Data Engineering by Coursera
• Microsoft Azure Databricks for Data Engineering by Microsoft
• Data Engineering with MS Azure Synapse Apache Spark Pools by Microsoft

There are various platforms where you can study Data Engineering courses with a certificate at the end of the course duration. Some top choices include Coursera, Udemy, edX, Simplilearn, Great Learning, Databricks, LinkedIn Learning, Google Cloud, etc. Most of the students find these platforms convenient and affordable, and hence they are the topmost go-to options for learning everything about creating data pipelines and managing data warehouses.

You will come across several Data Engineering courses at the intermediate and advanced levels that actively include real projects with big data tools. The projects usually revolve around building ETL pipelines, data processing systems and pipelines.

Project work actually allows you to apply your theoretical knowledge hands-on to data modelling and data pipeline designing, assessing your practical understanding and adding value to your project portfolio. To make sure that there is project-based learning included in the course modules, you should always check the course structure of Data Engineering courses.

Of course, yes. Machine learning algorithms are an integral part of the Data Engineering syllabus modules, as they come in handy at the time of data modeling, scaling, and optimization and when collaborating with data scientists and machine learning engineers. Building data infrastructure involves many ML-integration initiatives to meet specific data requirements, and hence, you should have a strong hold over machine learning techniques.

The Data Engineering curriculum is not the same for all online certifications. A few core concepts related to databases and fundamentals of data modeling, warehousing, and machine learning can be the same, but the course focus differs, along with the study approach and user audience. Data Engineering courses for beginners are more basic and focus on theoretical learning, while advanced courses are practically oriented and involve complex processing and tasks.

Programming languages are foundational in building, managing, and optimizing data pipelines, data set processing and working with multiple data systems. Some important programming languages mostly covered in the Data Engineering coursework include Python, SQL, Java, Scala, R, etc. You must pay attention to your programming classes as they come in handy at the time of real-world database applications.

Unfortunately, no college in India offers a dedicated full-time course in Data Engineering at present. Colleges like IIT Kanpur, SRM Institute of Science and Technology, and BITS Pilani provide professional certificate and M.Tech courses in Data Engineering in the online mode, where the lectures are self-paced and convenient for you to take at whatever time suits you.

But, you can take up related courses like Data Science and CSE, which are offered across various top colleges, including the top IITs and other renowned engineering colleges in the full-time mode.

You can study a 5-month online Professional Certificate Course in Data Engineering offered by IIT Kanpur after completing your graduation in a related field. For the NITs, none of them offer a dedicated Data Engineering course as yet, but you can have a look at related courses like BTech in AI and Data Science or BTech CSE with some elective modules on Data Engineering basics.

You can land some exciting career opportunities after completing Data Engineering courses online, along with a healthy salary potential and job satisfaction score. Some top Data Engineering jobs are given here for your reference:

• Data Engineer
• Big Data Engineer
• Data Warehouse Engineer
• Machine Learning Engineer
• Cloud Data Engineer
• Data Analyst
• Data Architect
• Business Intelligence Developer

The starting Data Engineering salary for fresher students is around INR 4 LPA to INR 8 LPA, which differs on the basis of the job role, recruiter, company location, skill set, internship experience, and additional certifications (if any). After you gain some years of experience in the Data Engineering field, you can easily take home a hefty amount, given the need and scope of data modeling and infrastructure in small and large businesses.

Data Engineering jobs will not get fully replaced by AI or automation in the future but rather AI will transform the nature of jobs by automating mundane, repetitive tasks and letting data engineers focus on building more sophisticated data systems, AI models and infrastructure to power businesses.

In fact Data Engineering professionals can work faster and with more efficiency, strategically understanding business infrastructure needs and coming up with powerful data-driven pipelines for the future. So, you should up your game by enhancing your skill set and taking up skill-based certifications to stay relevant in the market.

Data engineers are in demand across various work fields for the effective management of data systems, risk analysis, fraud detection, and improved customer experiences. Some of the top industries that are putting in a lot of money on data infrastructure and analytics at present are given here:

• Technology
• Finance
• E-Commerce
• Healthcare
• Retail
• Consulting

Absolutely, yes. Internship experience is highly valuable in a practical and technical field like that of Data Engineering where you have to deal with large datasets, infrastructure, and warehouses. Internships give you the right set of skills and hands-on experience with data systems, tools, and workflows, along with excellent networking opportunities that can enhance your career prospects.

A deep knowledge of AI and ML is not a mandatory requirement for pursuing Data Engineering courses but you should be familiar with the basic fundamentals that further come in handy in the optimization of AI models along with the implementation of efficient data systems.

No doubt traditional Data Engineering is all about designing and building databases and warehouses along with robust pipeline infrastructures, ensuring the accuracy and reliability of data. But with technological advancements and AI coming into the picture specialised roles like AI Data Engineers are becoming popular. So, you need to up your level by learning AI and ML as much as possible through beginner online courses or YouTube videos for high-paying Data Engineering careers.