What is a Data Engineer – Salary, Roles & Responsibilities, and Skills You Need

Data Engineer

What is Data Engineering?

Data Engineering is a technical discipline that centers on the building and designing of systems for managing, collecting, storing, and analyzing big data at scale.

Every day we see data in so many forms like profile visits, click on the websites, bounce rates, and via so many mediums like marketing ads, social media posts, company financial books, etc. To make a system that allows for a free flow of data and management, data engineering comes to the rescue. 

Who is a Data Engineer and what does he/she/they do?

Data Engineers are the technical professionals who prepare data that can be used by data scientists for valuable decisions and strategies. 

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What does data engineer do

They design a data system or architecture based on the data they collect, store and analyze. The data architecture, they work with is an effective system that allows data scientists and business analysts to interpret or convert the data into something insightful or valuable.

What Does a Data Engineer Do?

A Data Engineer has the following tasks to do

  • Develop a system, algorithm to drive data-driven solutions
  • Administer, run, and keep a constant check on the data systems
  • Collect information or data that is significant to the business/ company/ client’s needs. 
  • Build new methods and tools for productive and efficient data procurement and analysis. 
  • Ensure the validation and the sources of acquired data. 
  • Align methods with a check on security protocols and government policies. 

Difference Between a Data Engineer and Data Scientists

There is often confusion between a data scientist and a data engineer. People tend to overlap their roles and significance in the industry. 

The skills can sometimes be common however, their job profile is different. 

A Data Scientist is an expert who collects, cleans, analyzes, and interprets data for insightful solutions. The solution concluded is based on factual data from valid sources and an efficient data analysis system. 

A Data Engineer is an expert who is responsible for creating a data architectural system and data for data scientists to glean information for strategic and insightful explanations. 

Let us look at the demand for data engineer’s role in the market. 

Data Engineer Demand in the Market

Everywhere you look there is data. History logs, Cache, Application data, marketing data, user information, and so much more. Data Engineer is that expert who creates a proper data pipeline for efficient procurement, management, storage, and access of that data. 

Every industry is dealing with data and requires data oil for the smooth functioning of operations. This in turn increases the demand for data engineers in the market. 

Data science might have been a desired and ideal role. However, the recent stats and reports suggest the emerging surge in demand for data engineering. 

According to DICE 2020 Tech Report, Data Engineering is the fastest-growing job in 2019, growing by 50% YoY.

The job outlook for data engineering looking out to be an accelerating graph with new job avenues and options for tech students. If you are an aspirant, job seeker, or even looking for a switch, Data Engineer is the talk of the town you need to be a part of. 

Looking at the demand and upcoming positive outlook, you must be wondering about the pay for data engineers?

Keep reading to dive into the in-depth details about the Data Engineer Salary in India. 

Data Engineer Salary

The increasing demand for the role of data engineers and the limited human workforce supply has consequently enhanced the pay for data engineers. 

The average base salary for a data engineer in India is ₹839,625 per annum. The data engineer salary can range from a minimum of 396k per annum to a maximum of 2 million per annum. 

Average salary for data engineer in india


This is a significantly good start and has a promising future as well. It is, however, to be noted that the average salary of a data engineer is affected by many factors like the years of experience working in this profile, employer, location, skillset.

Data Engineer Salary: Based on Experience

Experience in every industry is a crucial factor to recognize one employee’s potential in the field of work. Experience is the one thing that highlights your past with the profile and all your achievements and ascertained work.

More experience years will suggest higher income for you. It makes you a top candidate from a fresher who still has to learn the basics, and does not know the insider tricks and tips which you have gained over all the years of work. 

Look at the graph and the table below to see how experience as a factor plays in determining a higher pay for a data engineer. 

Number of years of experienceAverage Base Pay/year  (In INR)
Fresher (>1 year of experience)₹464,722
Early Career (1-4 years of experience)₹719,884
Mid-Career (5-9 years of experience)₹1,296,505
Experienced (<10 years of experience)₹1,878,772
data engineer salary graph by experience

Source: PayScale

Data Engineer Salary: Based on Location

Surprisingly, even in times of remote working location plays into account so much while deciding a pay structure for an employee. 

A data engineer at Bangalore that is also known as Silicon Valley of India can earn higher than a Data Engineer at Chandigarh. 

Location matters a lot. There is a reason why people move towards metropolitan cities for job opportunities as the influx of pay is better in those locations. 

Let us look at which locations are paying significantly better to data engineers in India. 

Bangalore, Karnataka

The average base salary for a Data Engineer in Bangalore is ₹942,885 per annum. 

Data Engineer Salary in Bangalore

Source: PayScale

Pune, Maharashtra

The average base salary for a Data Engineer in Pune is ₹865,618 per annum. 

Source: PayScale

Chennai, Tamil Nadu

The average base salary for a Data Engineer in Chennai is ₹817,425 per annum. 

Data Engineer Salary in Chennai

Source: PayScale

Mumbai, Maharashtra

The average base salary for a Data Engineer in Mumbai is  ₹724,980 per annum. 

Data Engineer Salary in Mumbai

Source: PayScale

Hyderabad, Andhra Pradesh

The average base salary for a Data Engineer in Hyderabad is ₹984,305 per annum. 

Data Engineer Salary in Hyderabad

Source: PayScale

Gurgaon, Haryana

The average base salary for a Data Engineer in Gurgaon is ₹987,847 per annum. 

Data Engineer Salary in Gurgaon

Source: PayScale

New Delhi, Delhi

The average base salary for a Data Engineer in New Delhi is ₹902,317 per annum. 

Source: PayScale

Kolkata, West Bengal

The average base salary for a Data Engineer in Kolkata is  ₹524,000 per annum. 

Data Engineer Salary in Kolkata

Source: PayScale

Ahmedabad, Gujrat

The average base salary for a Data Engineer in Ahmedabad is ₹450,000 per annum. 

Data Engineer Salary in Ahmedabad

Source: PayScale

Data Engineer Salary: Based on Employer

The job profile of a data engineer is in high demand by every industry. However, the company you are hired in will be a deciding factor in finalizing the average salary of a data engineer in India. 

Every company has different specifications and roles for a data engineer and the pay will be decided accordingly. 

First, let us look at some of the top recruiters in India.

Top 10 recruiters in India for Data Engineering

1. Amazon Inc, India

2. Deloitte

3. HCL Technologies Ltd. 

4. Cognizant

5. IBM India Private Ltd. 

6. Tata Consultancy Services

7. Accenture

8. Capgemini

9. Wipro Ltd. 

10. Infosys

Now let us look at the difference in average base pay for data engineers among all these top firms in India. 

CompaniesAverage Base Pay/year (In INR)
Amazon Inc₹1,937,775
HCL Technologies Ltd.₹975,000
IBM India Pvt. Ltd.₹709,859
Tata Consultancy Services₹700,000
Wipro Ltd.₹516,000

Source: PayScale

Data Engineer Salary: Based on Skill Set

To stand out from the crowd, a data engineer should be proficient in the skills required for the position. 

We will read about the Data Engineer Skills in detail below. 

As there is no end to learning and skills, you could make a target to learn skills required by your employer or the job role you are applying for. This will help you prioritize over other applicants. 

Look at the table below to get the gist of how different skills could vary the average pay base for a data engineer. 

SkillSetAverage Base Pay/year (In INR)
ETL (Extract, Transfer, Load) Tools₹876,079
Programming Language (Python)₹802,380
Apache Spark skills₹970,658
Cloud Computing₹1,100,000
Big Data Analytical Skills₹897,985

Source: PayScale

You could notice that skills like Big data analysis, Apache Spark skills, ETL tools, and cloud computing get a data engineer’s salary above the average base pay for a data engineer in India.

Therefore, upskill yourself accordingly. 

How to Become a Data Engineer

The Path to Become an excellent Data Engineer

  • Get Your Degree

Many technical jobs do not always require a degree. However, for a data engineer, an undergraduate degree in the relevant field is quite crucial. The degree could help you understand the basic concepts and key pointers about the domain of work as well. 

Data Engineering is a broad field and getting a degree is what going to help you master its wide spectrum. 

Also, many great companies make it a requirement to hire people with a relevant undergraduate degree. So, to make the first tick in becoming a data engineer, get yourself a degree. 

  • Master the skills required for Data Engineering

Every profession requires a set of skills to function properly. Data Engineering likewise, also requires certain skills SQL, NoSQL, knowledge of Data warehousing tools, programming languages like Python, Java, etc, understanding of relevant procedures and methodologies, and so much more. Mastering these skills will help a data engineer to perform their task to his/her full potential. In addition to this, it is always good to keep learning new skills every once in a while for your personal growth and development. 

  • Upskill with a certification course or specialization

There is never a bad day to learn something extra. To advance your career opportunities and growth, add to your skills a relevant specialization or master’s degree as well. 

Learning a relevant specialization gives you a different outlook for your domain of work thereby enhancing your capabilities and performance. 

A data engineer resume with good specialization courses could work well

during the interview process by standing different from the crowd. 

Learning courses on Tableau, automation, Kafka, Java, etc. could help you master this profession like a pro. 

  • Proficiency in Programming

The job profile of a data engineer as the name suggests is a combination of data analysis and engineering. It is like the best of both worlds (analytical and development). The role and skills are usually about designing and building data infrastructures. However, to enhance your working with the analytical tool and everything, programming languages will be like the cherry on the top. Finding a language to master could help you go a long way in becoming a good data engineer. 

It is a skill many employers find requisite before hiring a data engineer. 

  • Professional Growth = Personal Growth

The step towards becoming a good data engineer is to never forget that ‘excellence is not permanent.  You are good today but will not be tomorrow if stop your learning and growth. 

A bigger part of your personal growth relies on your professional advancement. If you are comfortable at one job and do not shift to another for better options, then you cannot become the best data engineer. 

It is always advisable to professionally keep leaping in your career. It will give you new experiences, new avenues to explore. 

  • Build your portfolio

A portfolio is a compilation of your work that highlights your skills, opinions, knowledge, and experience in your domain of work. It can be a series of projects, independent personal research, publications, work you did as an employee. 

A complete strategy goes on building a portfolio to showcase your full potential to the people hiring you. It is a crucial element as building a portfolio you learn many things along the process. 

  • Gain experience in your relevant field

Experience matters a lot while sitting for an interview. Not only does it gives an impression of who you are but also a significant factor in deciding the average base salary for a data engineer. 

Start with small companies as they can give you full exposure to an intense working system with many job roles assigned. You could learn time management skills and get a perspective into different industries. 

Pick up on independent freelance projects for self-learning and your portfolio. 

Gaining the right experience in your relevant field will give you the taste of your job profile and help you find out the right industry, tole, and responsibility you like the most. 

Let us now look at some of the skills required for data engineers. 

Data Engineer Skills Required

Data Engineer Skills

Data Engineering is an amalgamation of data science and software engineering. It requires skills from both disciplines thereby, broadening the scope of learning for a data engineer. 

Key Technical Skills Required to Become a Data Engineer Are:

Data Warehousing Solutions

Data Warehouse is a space that contains all data from current and historical sources. Data that is procured from different sources like ERP(Enterprise resource planning) software, CRM (customer relationship management) system, etc, is stored in large volumes at data warehouses. 

It is this data that is used for query, analysis, report management, and data mining. 

Therefore, having a clear knowledge of data warehouse house solutions is essential for efficient sourcing and analysis. 

Database Systems

For a clear representation, storage, and retrieval of information, a Database Management system is crucial. SQL and NoSQL for tabular and non-tabular databases is an essential skill a data engineer should have. Building databases and managing a large chunk of data effectively is the key to a great analysis procedure. 

Machine Learning

Data Engineers as we discussed above creates data pipelines for smooth functioning for a data scientist. To do that, a basic understanding of Machine Learning algorithms, which is used by a data scientist to predict trends based on historical and current data, can help a data engineer understand their needs better while designing and building a system. 

ETL Tools

ETL (Extract, Transfer, Load) is a complete process of data procurement (extract) from sources that are converted (transformed) into simplified terms for analysis and can be stored (loaded) in the data warehouses. 

A solid base in working with ETL tools like Microsoft SQL Server Integration Services, SAP Data Services, IBM InfoSphere DataStage, etc could help you perform the ETL process with efficiency and clarity. 

Programming Languages

Proficiency in programming languages like Python, Scala, Java, etc is essential to the learning process while building data infrastructures, or practicing satistical analysis and data modeling. Programming Languages can make working efficient, faster, and productive. 

Other Basic Technical Skills and Programs for Data Engineer are

  • Data API’s
  • Knowledge of Data Structures and Algorithms
  • Basic knowledge of Distributed Systems like Apache Spark Software
  • Cloud Computing skills

Soft skills

To become a successful data engineer, just hard skills do not suffice. One needs to have certain soft skills as well. Soft Skills present your behavior, attitude, and personality.

Some of the important soft skills required for a data engineer are

  • Communicative
  • Manages time judiciously
  • Analytical thinking process
  • Team Player
  • Problem Solver
  • Leadership Skills
  • Presentation Skills

Data Engineer Job Description

A Data Engineer is responsible for designing and creating data systems that aligned with the business/organization/industry goals. They are responsible for using statistical analysis methodologies, data structures and algorithms, and relevant tools and procedures for identifying trends and handling a big chunk of data. Data Engineers’ proficiency with technical skills like database systems, programming languages, ETL tools will make them accountable for creating a data pipeline that converts raw data into a valuable source of information. 

A Data engineer with good communication and presentation skills should collaborate with the team managers, employees, and interested parties for deliverables and learn about each of their expectations and demands from one another. For example, a data engineer should be aligned with a data scientist’s needs while creating a data system.  

Data Engineer Responsibilities and Duties

  • Gathering a large set of data that aligns with business requirements.
  • Designing and developing a new system/infrastructure that makes the extraction, transfer, load process efficient, faster, and secure.
  • Use latest technologies like Cloud computing, machine learning, etc or products to keep the data systems and data pipelines up to date. 
  • Identifying errors in the current system and configuring a new, effective solution. 
  • Apply statistical methodologies, algorithms, and data structures for data procurement and analysis.  
  • Administer the process of procurement, designing, test run, storage, and management of new and current data pipelines. 
  • Working with interested parties like stakeholders for any data-oriented queries and issues. 
  • Operate on the internal systems for a better functioning process like automating manual processes, or faster data delivery, or scalable business operations. 


A data engineer is the fastest-growing job position currently in the IT job profiles. There is surging high demand by various industries for a data engineer who has a combination of skills from both disciplines of data science and data engineering. 

The high demand for data engineers and lower supply of the workforce results in consequently, better pay structures for a data engineer than many other job positions in the tech industry. 

If you love analyzing, building data pipelines, managing databases with proficiency in technical skills, a data engineer is the right job profile for you. 


1. Is a Data Engineer a good job?

Yes, a Data engineer is one of the in-demand jobs currently. A data engineer is not only a good job position for personal growth and professional development, a data engineer’s salary in India is worth applying for this job. 

Great learning, high demand, and amazing pay. 

2. How to become a data engineer?

The path to becoming a data engineer is:

  • Get a Bachelor’s degree in Computer science and any other related field
  • Learn the relevant skills like programming languages, data warehousing solutions, ETL Tools, SQL, etc. 
  • Get a certification or specialization course for upskilling
  • Build a portfolio
  • Work to gain experience
  • Advance professionally in your career

3. What is the salary of a data engineer?

A Data engineer’s average salary in India is ₹839,625 per annum.

This amount is the average base pay for a data engineer and can vary according to the experience, location, job profile, and skill set of a data engineer. 

4. Can a data engineer become a data scientist?

Both of these positions are not interchangeable. Data engineer possesses more technical skill while a data scientist has more analytical skills. 

However, it would be easy for a data engineer to become a data scientist

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