Data Engineering is one of the fastest-growing tech careers in India. Companies like Flipkart, Swiggy, CRED, and Juspay are hiring data engineers at salaries ranging from ₹12 LPA at entry level to ₹50+ LPA for senior roles. But the interview process is rigorous, multi-layered, and often misunderstood.
This guide breaks down exactly what to expect—and how to prepare.
What Data Engineers Actually Do
A Data Engineer builds and maintains the infrastructure that makes data usable. Responsibilities typically include:
- Designing and building data pipelines (ETL/ELT)
- Managing data warehouses and data lakes
- Optimising query performance for analytics teams
- Ensuring data quality and availability
- Collaborating with Data Scientists and Analysts
In Indian tech companies, DEs often also manage cloud infrastructure (AWS, GCP, Azure) and work with streaming systems for real-time data.
The Typical DE Interview Process
| Round | Focus |
|---|---|
| Screening Call | Background, experience, fitment |
| SQL Round | Complex queries, window functions, optimisation |
| Python/Coding Round | Data manipulation, scripting, pandas/PySpark |
| System Design Round | Design a scalable data pipeline |
| Cloud/Tools Round | AWS/GCP services, Kafka, Airflow, dbt |
| Managerial Round | Past projects, teamwork, problem-solving approach |
SQL: The Most Important Skill to Master
Every data engineering interview in India starts with SQL. Not just basic queries—complex ones involving:
- Window functions (ROW_NUMBER, RANK, LAG, LEAD)
- CTEs and recursive queries
- Query optimisation and index usage
- Joins, subqueries, aggregations
- Handling NULLs and data type conversions
Sample Question:
“Write a query to find the second highest salary from each department.”
SELECT department, salary
FROM (
SELECT department, salary,
DENSE_RANK() OVER (PARTITION BY department ORDER BY salary DESC) AS rnk
FROM employees
) ranked
WHERE rnk = 2;
Practice SQL daily on platforms like LeetCode, HackerRank, and Mode Analytics.
Python and Data Processing Skills
Most Indian companies expect DEs to write clean Python for:
- Reading and writing data from S3, GCS, BigQuery
- Data validation and cleaning scripts
- Automating pipeline tasks
- Basic pandas/PySpark operations
Sample Question: “Write a PySpark job that reads a CSV, filters records where status = ‘active’, and writes the result to Parquet.”
System Design: The Differentiator at Senior Levels
For roles at ₹20 LPA+, system design is the key round. Expect questions like:
- “Design a real-time order tracking system for a food delivery app”
- “How would you build a data warehouse for an e-commerce company from scratch?”
- “Design a pipeline that processes 100 million events per day with less than 5-minute latency”
Use this framework to answer:
- Clarify requirements (batch vs. streaming, latency, volume)
- Choose appropriate tools (Kafka for streaming, Airflow for orchestration, dbt for transformation)
- Address storage (data lake vs. warehouse, partitioning strategy)
- Discuss failure handling and monitoring
Key Tools to Know
| Tool Category | Popular Tools in India |
|---|---|
| Orchestration | Apache Airflow, Prefect, Dagster |
| Streaming | Apache Kafka, Kinesis |
| Processing | Apache Spark, PySpark, dbt |
| Cloud | AWS (Redshift, Glue, S3), GCP (BigQuery, Dataflow) |
| Monitoring | Grafana, Datadog, CloudWatch |
Salaries for Data Engineers in India (2024)
| Experience | Salary Range |
|---|---|
| 0–2 years | ₹8–14 LPA |
| 3–5 years | ₹15–28 LPA |
| 6–10 years | ₹28–50 LPA |
| 10+ years / Staff DE | ₹50–80 LPA |
Source: AmbitionBox, Naukri.com Salary Insights 2024
References
- AmbitionBox Data Engineer Salaries India — https://www.ambitionbox.com/salaries/data-engineer-salaries
- Naukri.com Data Engineering Jobs 2024 — https://www.naukri.com/data-engineer-jobs
- Apache Airflow Documentation — https://airflow.apache.org/docs/
- dbt (Data Build Tool) Documentation — https://docs.getdbt.com/
- LeetCode SQL Practice — https://leetcode.com/problemset/database/