Calculate rolling 7-day average per product

Last updated: January 1, 2026

Quick Overview

Write a query to compute rolling 7-day average grouped by region, handling edge cases like nulls and duplicates.

JPMorgan
Data Manipulation (SQL/Python)
Data Scientist
JPMorgan
January 1, 2026
Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Medium

25

5

705 solved


Write a query to compute rolling 7-day average grouped by region, handling edge cases like nulls and duplicates.

JPMorgan 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
JOIN types and when to use each
Pandas vectorized operations and groupby
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Subqueries and correlated subqueries
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?
  • How would you optimize this query for a table with 100 million rows?
  • What would you do if this query needs to run every 5 minutes?
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