Calculate time to first action per region

Last updated: January 2, 2026

Quick Overview

Write a query to compute time to first action grouped by user, handling edge cases like nulls and duplicates.

PayPal
Data Manipulation (SQL/Python)
Data Scientist
PayPal
January 2, 2026
Data Scientist
Take-home Project
Data Manipulation (SQL/Python)
Medium

271

15

525 solved


Write a query to compute time to first action grouped by user, handling edge cases like nulls and duplicates.

PayPal 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
  • Use advanced SQL features: window functions, CTEs, subqueries
  • Write efficient queries that avoid common performance pitfalls
  • Handle complex data transformations with multiple joins and aggregations
  • Discuss indexing strategy and query optimization
  • Address data quality issues: duplicates, missing values, outliers
Key Topics to Cover
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Subqueries and correlated subqueries
Data cleaning and transformation
Date/time manipulation
Index optimization and query performance
Aggregate functions and GROUP BY
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
  • Can you rewrite this without using subqueries?
  • How would you handle this if the data was spread across multiple databases?
  • What would you do if this query needs to run every 5 minutes?
  • What indexes would you create to support this query?
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