What does a Data Engineer do?
A data engineer builds and maintains the pipelines and infrastructure that move, store and transform data so analysts and data scientists can use it reliably. In India they typically work with SQL, Python, Spark and cloud warehouses, designing ETL/ELT workflows, modelling data, and ensuring large datasets are clean, governed, performant and available when downstream teams need them.
A data engineer usually has around 1–8 yrs of experience and earns typically ₹6L–₹28L/yr in India. The day-to-day blends SQL, Python, Apache Spark and more — this page gives you a ready-to-use data engineer job description template you can copy, plus the exact skills and salary employers expect.
Data Engineer job description template
Copy the 8 responsibilities, 5 requirements and 9 skills below into your job post, then edit the parts that are specific to your company — pay band, location and reporting line.
Select the text above to copy it manually if the button is unavailable.
What are a Data Engineer's key responsibilities?
A data engineer is typically responsible for the 8 duties below, which cover the day-to-day work most employers expect the role to own outright. Paste them into your job post as they are, or cut the ones another team already handles — a responsibility list that claims work the hire will not actually do is the fastest way to lose a candidate at offer stage:
- Design, build and maintain ETL/ELT pipelines that ingest and transform data
- Model and manage data warehouses and lakes for analytical workloads
- Optimise large-scale data processing with Spark or distributed systems
- Ensure data quality, lineage and governance across the platform
- Orchestrate workflows with tools like Airflow and monitor pipeline health
- Integrate data from APIs, databases, streams and third-party sources
- Tune query and storage performance to control cost and latency
- Partner with analysts and data scientists on schema and data needs
What qualifications does a Data Engineer need?
Employers hiring a data engineer in India usually ask for the 5 qualifications below, typically alongside 1–8 yrs of experience. Keep only the ones you will genuinely screen on: every extra must-have narrows the pool, and in the Indian market a long mandatory list filters out strong candidates whose background simply reads differently on paper:
- Strong SQL and proficiency in Python or Scala
- Experience with data warehouses (Snowflake/BigQuery/Redshift) and ETL tools
- Familiarity with big-data frameworks such as Spark and orchestration with Airflow
- Understanding of data modelling, partitioning and pipeline reliability
- Working knowledge of a cloud platform (AWS, GCP or Azure)
What skills should a Data Engineer have?
These are the 9 skills employers name most often on live data engineer listings in India. Treat the first few as the ones worth screening for directly and the rest as signals a candidate can pick up on the job — asking for all of them at once is what turns a reasonable role into an unfillable one:
Listing the three or four skills you genuinely screen on — rather than all 9 — is what keeps a data engineer posting from filtering out candidates who could do the job.
What does a Data Engineer earn in India?
Typical salary (India)
typically ₹6L–₹28L/yr
Experience range
1–8 yrs
These are typical ranges and vary by city, company and skills. For live, role-specific pay data, see the OnJob salary guide.
Data Engineer job description — FAQs
What does a data engineer do?
A data engineer builds the pipelines and infrastructure that collect, store and transform data so it's reliable and ready for analysis. Day to day that means writing ETL jobs, modelling warehouses, orchestrating workflows and keeping data quality high.
What is the difference between a data engineer and a data analyst?
A data engineer builds and maintains the data infrastructure and pipelines; a data analyst uses the resulting data to answer business questions. Engineers make data usable and reliable; analysts turn it into insight.
What tools do data engineers use in India?
Common tools include SQL, Python, Apache Spark for big data, Airflow for orchestration, and cloud warehouses like Snowflake, BigQuery or Redshift. Knowledge of Kafka and a cloud platform is a strong plus.
How much does a data engineer earn in India?
Data engineers in India typically earn ₹6L–₹11L per year at entry level, ₹13L–₹20L at mid-level, and ₹24L+ once senior. Compensation tends to follow platform scale: tuning Spark over large datasets, modelling warehouses on Snowflake, BigQuery or Redshift, orchestrating with Airflow, and moving streams through Kafka on AWS, GCP or Azure while keeping lineage and cost under control. Typical postings ask for 1–8 years.