Calculate time to first action per user

Last updated: October 24, 2025

Quick Overview

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

Postmates
Data Manipulation (SQL/Python)
Data Scientist
Postmates
October 24, 2025
Data Scientist
Phone Screen
Data Manipulation (SQL/Python)
Medium

56

7

1,749 solved


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

This question from Postmates's Phone Screen tests practical data skills. The interviewer wants to see clean, efficient queries that handle edge cases like NULLs, duplicates, and large datasets.

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
Index optimization and query performance
Date/time manipulation
JOIN types and when to use each
NULL handling and COALESCE
Data cleaning and transformation
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 this if the data was spread across multiple databases?
  • What indexes would you create to support this query?
  • How would you validate the correctness of your query results?
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