Data Engineer - GCH
Zensar
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This role on the market
9,774 open data roles across 978 companies are on ApplySarthi right now, most of them in Bengaluru (523), Hyderabad (354), Mumbai (158).
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What data roles keep asking for: Python (38%), SQL (33%), AWS (29%), Machine learning (19%), Spark (15%), Databricks (14%), Azure (13%), Stakeholder management (13%) — counted across their open postings here.
Data Engineer jobs in India · Remote Data Engineer jobs · AWS jobs · Airflow jobs · Azure jobs · CI/CD jobs
Zensar has 266 open roles listed here.
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Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for data roles keep coming back to Python, SQL, AWS, Machine learning. Practise those questions before you sit with Zensar.
Questions you are likely to be asked
- Why do you want to join Zensar?
- What is your experience with Databricks? Tell me one thing you learned the hard way.
- When would you not use machine learning for a problem?
- Walk me through a model you built, from the data to how it was used.
- How did you know your model was actually good, and not just good on your test set?
Prep Sarthi gives you a free mock interview: an AI interviewer asks you questions like these out loud, from your own CV and this job, and shows your score and your weakest answer.
Practise the Data Engineer - GCH at Zensar interview free →1. Data Engineer: Core Skills and Knowledge: - 7-9 years of experience in data engineering. - Hands-on experience with Databricks (Delta Lake, notebooks, Databricks Workflows). - Strong programming skills in Python and SQL. - Working knowledge of Apache Spark (PySpark preferred) for data transformation. - Experience with either AWS (S3, Glue, EMR) or Azure (ADLS Gen2, Data Factory, Synapse) services. - Understanding of data modeling concepts (star schema, dimensional modeling). - Familiarity with version control (Git) and basic CI/CD practices. Desirable Skills: - Databricks Certified Data Engineer Associate (or working toward it). - Exposure to streaming data pipelines (Structured Streaming, Kafka, Kinesis, or Event Hubs). - Familiarity with orchestration tools (Airflow, Databricks Workflows). - Basic understanding of data governance and security practices (PII masking, access control). - Exposure to Power BI or other BI tools for understanding downstream
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Listed on oraclehcm · posted 2026-09-25. ApplySarthi collects openings and links to application pages; the role is advertised by Zensar, not by us.