Calculate rolling 7-day average per user

Last updated: March 10, 2026

Quick Overview

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

DE Shaw
Data Manipulation (SQL/Python)
Data Scientist
DE Shaw
March 10, 2026
Data Scientist
Onsite
Data Manipulation (SQL/Python)
Medium

249

6

3,332 solved


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

This question from DE Shaw's Onsite 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
NULL handling and COALESCE
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
  • What would you do if this query needs to run every 5 minutes?
  • How would you validate the correctness of your query results?
  • How would you handle slowly changing dimensions in this scenario?
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Sample Answer
Approach

Break the problem into logical steps before writing SQL. Think about: 1. What tables do I need to join and on which keys? 2. What filtering (WHERE) d...

Solution Pattern

```sql WITH filtered_data AS ( SELECT * FROM main_table WHERE condition = 'value' AND date_col >= '2024-01-01' ), aggregated AS ( SELECT ...


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