Data Engineering Interview Prep
Practice data engineering interviews out loud. Design pipelines, explain SQL reasoning, and defend architecture trade-offs with an AI interviewer that pushes back like a real senior DE.
Start a Data Engineering InterviewWhat it tests
- Pipeline & architecture design — ingestion strategy, batch vs streaming, storage layer trade-offs, orchestration
- SQL reasoning — explain query optimization out loud, walk through window functions, schema design decisions
- Reliability thinking — idempotency, schema evolution, backfill strategy, data quality gates
- Tooling trade-offs — Airflow vs Prefect, dbt, Kafka, Spark, Snowflake — with rationale
Meet Alex, your interviewer
Alex is a senior data engineer archetype modeled on hiring bar at Databricks, dbt Labs, and Snowflake. Alex expects you to drive the design, probes on failure modes and scale, and asks why at every decision point. No hand-holding — just the real interview.
Sample interview questions
- 1.Design a real-time event ingestion pipeline for 10 million events per second.
- 2.Walk me through how you'd design the schema for a data warehouse serving both analytics and ML features.
- 3.A dbt job failed halfway through. How do you ensure the data isn't corrupted?
- 4.Explain the trade-off between a data lake and a data warehouse for this use case.
- 5.How do you handle schema evolution when upstream sources add columns without notice?
Ready to practice?
Free to start. No credit card required.