The median Big Data Engineer (Hadoop/Spark) salary in India is ₹14.7L in 2026, with a typical range from ₹14.2L to ₹15.4L. Pay has moved +10.0% year-on-year. Bengaluru currently leads city pay at ₹16L. This is base salary for permanent employees.
What does A Big Data Engineer (Hadoop/Spark) do?
A Big Data Engineer (Hadoop/Spark) is responsible for building and operating large-scale batch and streaming data platforms on Hadoop, Spark, and related distributed systems for organizations processing petabyte-scale datasets.
Day-to-day responsibilities
Permanent salary benchmarks for Big Data Engineer (Hadoop/Spark) in India, from the low end to the top of the range, based on published market compensation data.
₹14.7L
national median per year
+10.0% year on year
Moderate evidence · India annual benchmark · 2026 data · How we check our numbers
Seniority is the biggest single driver of Big Data Engineer (Hadoop/Spark) pay in India. Entry-level roles start at ₹6.9L, rising 500% to ₹41.4L at lead or principal level.
Junior
₹6.9L
₹6.9L-₹6.9L middle band
Mid-level
₹14.7L
₹14.7L-₹14.7L middle band
Senior
₹24.8L
₹24.8L-₹24.8L middle band
Principal/Lead
₹41.4L
₹41.4L-₹41.4L middle band
Certain technical skills push Big Data Engineer (Hadoop/Spark) salaries in India significantly above the ₹14.7L median. These are the most impactful skills to develop or highlight when negotiating.
Apache Spark (PySpark/Scala)
+16%
salary premium vs median
Hadoop ecosystem (HDFS, Hive, YARN)
+10%
salary premium vs median
Kafka for streaming pipelines
+14%
salary premium vs median
Cloud data platforms (EMR, Databricks, HDInsight)
+15%
salary premium vs median
How much does a Big Data Engineer (Hadoop/Spark) earn by city in India?
Big Data Engineer (Hadoop/Spark) salary varies meaningfully by location. Bengaluru pays the most at ₹16L (9% above the national benchmark), while Pune sits at ₹13.4L (9% below the national benchmark). Location is worth factoring into any offer negotiation.
After Income Tax & Cess · single, standard payroll deductions
Gross/year
₹14.2L
Take-home/year
₹13,38,356
Per month
₹1,11,530
Effective rate
6.0%
Gross/year
₹14.7L
Take-home/year
₹13,78,868
Per month
₹1,14,906
Effective rate
6.3%
Gross/year
₹15.4L
Take-home/year
₹14,32,884
Per month
₹1,19,407
Effective rate
6.7%
See the full band-by-band breakdown for Big Data Engineer (Hadoop/Spark)
Adjust for your actual salary, see each Income Tax (New Regime) and 4% health & education cess band, and get monthly and weekly figures.
Contract day rates available for this role
Median ₹10,140/day, see full breakdown, city rates, and take-home calculator
Market Demand & Outlook
Demand level
Low
Based on hiring signals relative to similar roles in this market.
Top hiring locations
Career outlook
Strong upward salary momentum
Big Data Engineer (Hadoop/Spark) salaries are showing strong movement, with latest benchmark growth at +10.0%.
Compare this role
Compare adjacent roles, employer estimates, published agency guides, and an offer against the market before you make a decision.
Explore India salary intelligence
Market context for Big Data Engineer (Hadoop/Spark)s in India
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Big Data Engineer (Hadoop/Spark)s in India earn a median salary of ₹14.7L in 2026, with a typical range from ₹14.2L at the 25th percentile to ₹15.4L at the 75th percentile. This benchmark reflects published market compensation data for annual pay across the India market.
Bengaluru currently leads city pay at ₹16L, which is 9% above the national benchmark. City coverage for this role includes Bengaluru, Hyderabad, Delhi NCR, Pune, Mumbai, helping you compare local pay differences without needing separate city-role pages.
At experience level, entry roles start around ₹6.9L, senior roles sit near ₹24.8L, and lead-level roles reach about ₹41.4L. Demand is currently moderate for this role based on recent coverage and salary momentum signals.
The median Big Data Engineer (Hadoop/Spark) salary in India is ₹14.7L in 2026. The typical range runs from ₹14.2L at the 25th percentile to ₹15.4L at the 75th percentile, based on published market compensation data.
Big Data Engineer (Hadoop/Spark) salaries have moved +10.0% year-on-year in India.
Big Data Engineer (Hadoop/Spark) salaries vary across India. Bengaluru leads at ₹16L (+9% vs the national benchmark), while Pune sits at ₹13.4L. Use the city breakdown above to compare all locations.
A Big Data Engineer (Hadoop/Spark) earning the median ₹14.7L gross in India will take home a net amount after income tax and other deductions. Use the PayMetric Labs take-home calculator on this page for an exact breakdown by tax band.
Principal/Lead-level Big Data Engineer (Hadoop/Spark)s in India earn the most, with a median of ₹41.4L, compared to ₹6.9L at entry level. Seniority is the strongest single driver of pay in this role.
This benchmark is derived from verified market compensation data and is rated Moderate Confidence. High Confidence means the benchmark is corroborated across independent sources and is citation-ready. Moderate Confidence is directional context while coverage is still building. Limited Market Data means early signals only.
An indicative year-over-year signal of +10.0% is available from the latest market research for this role. This figure is directional market research rather than a matched prior-year observation in our own dataset.
Candidates should compare offers against the ₹14.2L-₹15.4L middle-market band, while employers should treat ₹14.7L as the current market midpoint for this role.