Data Engineering Interview Guide (2026 Edition)
Everything you need to know for a data engineering interview: SQL, pipeline design, system design, and behavioural questions.
Data engineering interviews in 2026 test four core areas: SQL proficiency, data modelling, pipeline architecture, and system design.
SQL is still the #1 tested skill. Focus on window functions (ROW_NUMBER, RANK, LAG/LEAD), CTEs (especially recursive), and query optimisation (EXPLAIN ANALYZE, indexing strategies, BRIN vs B-Tree).
For pipeline design, know batch vs streaming trade-offs, idempotency patterns, and the Medallion architecture (bronze/silver/gold). Airflow is the most common orchestrator — know DAGs, operators, and XCom.
dbt has become essential. Understand refs, sources, materializations (especially incremental with unique_key), and the staging → intermediate → marts layer pattern.
System design questions typically ask you to design a data warehouse, real-time analytics pipeline, or ETL system. Use the framework: clarify requirements → sketch data flow → justify technology choices → discuss failure modes.
Start practicing with our Data Engineering career path — it covers all of this with quizzes, lessons, and system design walkthroughs.