Join users and rides to find rolling 7-day average

Last updated: February 16, 2026

Quick Overview

Write a query joining users and users to produce the combined rolling 7-day average.

Zillow
Data Manipulation (SQL/Python)
Data Scientist
Zillow
February 16, 2026
Data Scientist
Take-home Project
Data Manipulation (SQL/Python)
Hard

60

14

1,544 solved


Write a query joining users and users to produce the combined rolling 7-day average.

Zillow 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
  • Solve complex analytical problems with elegant, readable SQL
  • Optimize queries for large-scale datasets with partitioning and indexing
  • Use recursive CTEs, lateral joins, and advanced window functions
  • Design the data model alongside the query solution
  • Discuss trade-offs between SQL and programmatic approaches (Python/pandas)
  • Consider the operational aspects: query scheduling, incremental processing
Key Topics to Cover
Data cleaning and transformation
JOIN types and when to use each
Common Table Expressions (CTEs)
Aggregate functions and GROUP BY
Index optimization and query performance
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 indexes would you create to support this query?
  • How would you optimize this query for a table with 100 million rows?
  • Can you rewrite this without using subqueries?
  • How would you handle slowly changing dimensions in this scenario?
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