Google Data Engineer Interview Questions & Practice
Google Data Engineering interviews emphasise strong SQL (BigQuery-style analytics), Python coding, and large-scale pipeline design (Dataflow/Beam concepts). Work through the question styles below with instant grading.
Practice challenges
- Word Frequency Counter (python, easy, +50 XP)
- Find Duplicate Emails (sql, easy, +50 XP)
- Second Highest Salary (sql, easy, +50 XP)
- Validate Unique User IDs (python, easy, +50 XP)
- ROW_NUMBER: Assign Unique Rank to Each Employee (sql, easy, +50 XP)
- RANK: Rank Employees by Salary (With Gaps) (sql, easy, +50 XP)
- DENSE_RANK: Rank Employees Without Gaps (sql, easy, +50 XP)
- RANK vs DENSE_RANK: See the Difference Side by Side (sql, easy, +50 XP)
- SUM OVER: Show Grand Total on Every Row (sql, easy, +50 XP)
- LAG: Show Previous Day's Sales Amount (sql, easy, +50 XP)
- LAG: Calculate Day-Over-Day Sales Change (sql, easy, +50 XP)
- LEAD: Detect Days Where Sales Will Increase Next Day (sql, easy, +50 XP)
- FIRST_VALUE: Show Highest Salary in Each Department for Every Employee (sql, easy, +50 XP)
- ROW_NUMBER: Remove Duplicate Rows and Keep One Per Order (sql, easy, +50 XP)
- Customers Who Never Placed an Order (sql, easy, +50 XP)
- Find Average Order Amount for Each Customer (sql, easy, +50 XP)
- Find the Most Recent Order Date for Each Customer (sql, easy, +50 XP)
- Find the Customer Who Placed the Most Orders (sql, easy, +50 XP)
- Departments With More Than 2 Employees (HAVING) (sql, easy, +50 XP)
- Find the Average Rating of Each Product (sql, easy, +50 XP)
What SQL level does Google expect for data roles?
Advanced analytical SQL: window functions, arrays/structs thinking, deduplication, and cost-aware query design. The window-function challenges below are the right practice.
Is Python required for Google Data Engineer roles?
Yes — expect at least one coding round with Python data-structure and parsing problems, similar to the Python set on this page.
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