Data Engineering Interview Questions & Assessment
Evaluate data engineering skills including ETL pipelines, data warehousing, streaming, Apache Spark, and data modeling.
Why Data Engineering Matters
Data engineers build the infrastructure that powers analytics and ML. They are in high demand as companies generate more data and need reliable pipelines to process it.
Sample Interview Questions
Explain the difference between ETL and ELT. When would you choose each?
Design a data pipeline that processes 100M events per day. What tools would you use?
What is a star schema? Compare it with a snowflake schema.
How does Apache Spark handle data partitioning? Explain shuffles and their impact.
What is data quality? How would you implement data quality checks in a pipeline?
How to Prepare
Know SQL deeply — it is the primary tool for data engineers
Understand data modeling: dimensional modeling, data vault, wide tables
Practice with Apache Spark or Databricks
Know orchestration tools: Airflow, Dagster, Prefect
Understand data warehouse architectures: Snowflake, BigQuery, Redshift
Related Skills
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