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Staff Engineer - Data Engineer

Nagarro

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This role on the market

7,303 open data roles across 663 companies are on ApplySarthi right now, most of them in Bengaluru (417), Hyderabad (310), Mumbai (156).

What data roles keep asking for: AWS (25%), SQL (23%), Python (22%), Machine learning (12%) — counted across their open postings here.

BigQuery jobs · Databricks jobs · LLMs jobs · SQL jobs

Nagarro has 881 open roles listed here.

Counted across 14 company job boards, updated as roles open and close.

Preparing for this interview

Interviews for data roles keep coming back to AWS, SQL, Python, Machine learning. Practise those questions before you sit with Nagarro.

Questions you are likely to be asked

  1. Why do you want to join Nagarro?
  2. What is your experience with dbt? Tell me one thing you learned the hard way.
  3. What would you check first if a model's accuracy dropped after going live?
  4. When would you not use machine learning for a problem?
  5. Walk me through a model you built, from the data to how it was used.

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 Staff Engineer - Data Engineer at Nagarro interview free →

6+ years of experience in Data Engineering, Analytics Engineering, or related fields. 3+ years of hands-on experience with dbt in production environments. Strong expertise in SQL and complex data transformation development. Strong understanding of dbt Core and/or dbt Cloud. Experience with dbt, including dbt models and materialization Incremental models Macros and Jinja dbt tests and data quality frameworks Snapshots Seeds and sources Documentation and lineage dbt packages Strong experience with at least one cloud data platform, such as: Snowflake Databricks BigQuery Amazon Redshif ​​​​​​​ AI skills (required for all roles) Daily, fluent use of Claude Code and/or GitHub Copilot for implementation, refactoring, test generation, and code review Ability to establish team standards for AI-assisted development: effective prompting, trust-vs-verify discipline on generated code, security/IP guardrails, and reviewing AI-authored changes Working understanding of LLM fundamentals: context windows, tokens, model selection, and prompt/context engineering Experience integrating AI into developer workflows and agentic/automation tooling (MCP servers, AI-driven CI steps, codegen and doc-generation pipelines) Able to evaluate AI tooling pragmatically: measuring real productivity and quality impact, not hype

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Listed on smartrecruiters · posted 2026-09-08. ApplySarthi collects openings and links to application pages; the role is advertised by Nagarro, not by us.