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Pune · IT services, automotive and semiconductor hub

Data Engineer resume for Pune jobs

Build an ATS-optimised data engineer resume tailored for Pune's job market. Data Engineers in Pune earn ₹4L – ₹32L — CV Prime tailors your resume to each JD, scores your ATS match, and exports a clean PDF.

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Data Engineer salary in Pune

₹4L – ₹32L

Pune is a fast-growing tech and core-engineering market for data engineers. Pay scales with experience, company type, and your strongest skills.

Full Data Engineer salary guide (fresher to senior)

Who's hiring data engineers in Pune

Pune is built on it services, automotive & ev, semiconductor and more. CV Prime knows the ATS formats these employers use.

Major Pune employers

InfosysPersistentBajaj AutoQualcommCumminsMahindra

Companies hiring Data Engineers

FlipkartAmazon IndiaSwiggyZomatoPhonePeGrowwFractal AnalyticsTiger AnalyticsMu SigmaZepto

Pune's key sectors for this role

IT services

Automotive & EV

Semiconductor

BFSI

Manufacturing

ATS in Pune: Pune IT and engineering firms value precise technical keywords — for automotive roles, terms like AUTOSAR and ISO 26262 matter. Keep it single-column and specific.

ATS keywords for data engineers

Pune recruiters screen for these. CV Prime checks your resume against them and the exact JD automatically.

Apache SparkAirflowdbtKafkaPythonSQLBigQuerySnowflakeAWS GlueDatabricks

Why Pune data engineers use CV Prime

Tailored to each JD

Paste any Pune data engineer job description and AI rewrites your resume to match it — keywords, bullets, and summary.

Benchmarked to local pay

Know the Pune salary band for data engineers (₹4L – ₹32L) so you apply and negotiate with real data.

ATS-safe for local employers

Pune IT and engineering firms value precise technical keywords — for automotive roles, terms like AUTOSAR and ISO 26262 matter. Keep it single-column and specific.

Data Engineer resume in Pune — FAQ

What is the average data engineer salary in Pune?

In Pune, data engineers earn ₹4L – ₹32L. Pune is a fast-growing tech and core-engineering market for this kind of role. Your exact pay depends on your years of experience, the company type (startup vs MNC vs product tier-1), and the depth of your in-demand skills. See the full breakdown on the Data Engineer salary guide.

Which companies hire data engineers in Pune?

Pune's data engineer market is driven by it services, automotive and semiconductor hub, with major employers including Infosys, Persistent, Bajaj Auto, Qualcomm, Cummins, alongside companies like Flipkart, Amazon India, Swiggy, Zomato. CV Prime tailors your resume to each company's job description and scores your ATS match before you apply.

What is the difference between a data engineer and a data scientist in India, and which pays more?

Data engineers build and maintain the infrastructure that delivers clean, reliable data — pipelines, warehouses, orchestration systems. Data scientists consume this data to build models, run experiments, and generate insights. In India in 2026, senior data engineers with deep distributed systems experience (Spark, Kafka, Databricks) often match or exceed data scientist salaries, particularly at product and fintech companies. Data scientists with ML deployment and production model experience tend to earn more at AI-first companies. Both tracks are well-compensated relative to general software engineering, with senior salaries in the ₹30L–₹60L range at top-tier companies.

What are the most important skills for a data engineer to have in India in 2026?

The modern data engineering stack in India centres on: Python for pipeline code, SQL for transformation logic, Apache Spark or Databricks for large-scale processing, Apache Airflow for orchestration, dbt for transformation layer management, and a cloud data warehouse (Snowflake or BigQuery). Kafka or Kinesis is increasingly expected for streaming pipelines. Cloud platform proficiency (AWS or GCP) is effectively mandatory. Data quality tooling (dbt tests, Great Expectations) is becoming a strong differentiator. Candidates who can design end-to-end data architectures — not just implement individual pipelines — command significant salary premiums.

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