Data engineer interview questions by company

Interview guides for data engineers: reported rounds, difficulty and questions from candidates, company by company. Free to read.

Data engineering interviews centre on SQL, data modelling and pipelines that keep working when the data is late, wrong or huge. Expect window functions and joins, schema design for a warehouse, batch versus streaming trade-offs, Spark or similar engines, and orchestration with tools such as Airflow.

Loops often combine a SQL screen, a coding round in Python, a pipeline design round and a behavioral round. In the design round you may be asked to build an ingestion pipeline for a new data source, handle late events, or keep a metric consistent across teams. Clear thinking about data quality and failure handling earns more credit than naming tools.

Each guide below lists the rounds, difficulty and questions that candidates reported for that company, from public sources. Guides for India-based companies come first, then global companies. PortLume AI is unofficial and not affiliated with any company named.

India product companies

IT services and consulting

Global big tech and product companies

Questions about these guides

What do data engineer interviews usually cover?

SQL, data modelling, pipeline design, Python, distributed processing such as Spark, orchestration and data quality. Senior roles add architecture and cost trade-offs.

How hard is the SQL round?

Expect joins, aggregations and window functions on messy data. Practice reading a schema fast and explaining your query.

Do I need to know streaming?

It helps, and many roles ask about it. Be ready to explain batch versus streaming, late data and exactly-once ideas in plain words.

Are these guides official?

No. They are unofficial and built from public candidate reports.

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