Join orders and events to find engagement score

Last updated: October 15, 2025

Quick Overview

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

Visa
Data Manipulation (SQL/Python)
Data Scientist
Visa
October 15, 2025
Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Hard

16

6

1,547 solved


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

This question from Visa's Technical Screen 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
  • 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
NULL handling and COALESCE
Index optimization and query performance
JOIN types and when to use each
Aggregate functions and GROUP BY
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 indexes would you create to support this query?
  • What would you do if this query needs to run every 5 minutes?
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