Join users and messages to find engagement score

Last updated: March 9, 2026

Quick Overview

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

Instacart
Data Manipulation (SQL/Python)
Data Scientist
Instacart
March 9, 2026
Data Scientist
Phone Screen
Data Manipulation (SQL/Python)
Medium

7

12

3,923 solved


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

Data manipulation questions at Instacart test your ability to work with real-world datasets. This Phone Screen 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
Date/time manipulation
Index optimization and query performance
Aggregate functions and GROUP BY
Common Table Expressions (CTEs)
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 handle slowly changing dimensions in this scenario?
  • Can you rewrite this without using subqueries?
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Practice SQL Problems
Sample Answer
Problem Understanding

In this problem, we need to analyze the engagement score of users by joining two tables: users and impressions. The users table contains user-specific information, such as user ID, user name, an...

Approach
  1. Identify Relevant Columns: Determine the necessary columns from both users and impressions. For instance, user ID from users and impression type/timestamp from impressions.
  2. **Join Ta...

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