Calculate engagement score per region

Last updated: August 29, 2025

Quick Overview

Write a query to compute engagement score grouped by user, handling edge cases like nulls and duplicates.

Supabase
Data Manipulation (SQL/Python)
Data Scientist
Supabase
August 29, 2025
Data Scientist
Take-home Project
Data Manipulation (SQL/Python)
Easy

78

8

564 solved


Write a query to compute engagement score grouped by user, handling edge cases like nulls and duplicates.

Supabase asks this during the Take-home Project because data engineering skills are critical for the role. You should be comfortable with complex joins, window functions, CTEs, and performance optimization.

What the Interviewer Expects
  • Write syntactically correct SQL with proper JOIN and WHERE clauses
  • Use GROUP BY and aggregate functions appropriately
  • Handle NULL values correctly in your queries
  • Explain the query execution plan at a high level
Key Topics to Cover
Data cleaning and transformation
Index optimization and query performance
NULL handling and COALESCE
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Subqueries and correlated subqueries
Date/time manipulation
How to Approach This
  1. Clarify the schema and expected output format before writing queries.
  2. Use CTEs (WITH clauses) to break complex queries into readable steps.
  3. Consider window functions (ROW_NUMBER, RANK, LAG, LEAD) for ranking and sequential analysis.
  4. Watch for NULLs, duplicates, and edge cases in JOINs and GROUP BY.
  5. For pandas, prefer vectorized operations over row-by-row iteration.
Possible Follow-up Questions
  • How would you handle slowly changing dimensions in this scenario?
  • How would you handle this if the data was spread across multiple databases?
  • Can you rewrite this without using subqueries?
  • How would you validate the correctness of your query results?
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