Google data engineer interview guide
Google data engineering interviews put more weight on general coding ability alongside SQL and design. Expect clean, well-tested Python and schemas that scale.
Interview rounds
Python / coding round
Algorithmic and data-processing problems — clean code, complexity and edge cases matter.
Practice Python problems →SQL round
Multi-step queries with CTEs, window functions and careful NULL handling.
Practice SQL problems →Data modeling round
Model an application (for example a classroom or booking product) with clear relationships and keys.
Practice data modeling →Pipeline / system design round
Design distributed pipelines with partitioning, late data and cost in mind.
Practice system design →Sample Google interview questions
- Design the schema for a Google Classroom-style product.
- Write a query for the second-highest salary per department.
- Flatten nested JSON events into tabular rows in Python.
Tips to pass
- Write tests or walk through examples before you finish.
- Mention complexity for every coding answer.
- Watch the NOT IN / NULL trap in SQL.
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