Join sessions and sessions to find time to first action

Last updated: August 2, 2025

Quick Overview

Write a query joining sessions and messages to produce the combined time to first action.

Shopify
Data Manipulation (SQL/Python)
Data Scientist
Shopify
August 2, 2025
Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Medium

422

5

3,059 solved


Write a query joining sessions and messages to produce the combined time to first action.

Shopify asks this during the Technical Screen 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
Aggregate functions and GROUP BY
Date/time manipulation
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Common Table Expressions (CTEs)
NULL handling and COALESCE
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?
  • Can you rewrite this without using subqueries?
  • How would you handle slowly changing dimensions in this scenario?
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