Join users and clicks to find engagement score

Last updated: August 10, 2025

Quick Overview

Write a query joining users and users to produce the combined engagement score.

Netflix
Data Manipulation (SQL/Python)
Data Scientist
Netflix
August 10, 2025
Data Scientist
Take-home Project
Data Manipulation (SQL/Python)
Medium

87

7

4,421 solved


Write a query joining users and users to produce the combined engagement score.

Data manipulation questions at Netflix test your ability to work with real-world datasets. This Take-home Project question evaluates your SQL proficiency, understanding of data modeling, and ability to derive insights from raw data.

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
Pandas vectorized operations and groupby
Subqueries and correlated subqueries
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
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 slowly changing dimensions in this scenario?
  • How would you optimize this query for a table with 100 million rows?
  • How would you validate the correctness of your query results?
  • Can you rewrite this without using subqueries?
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