Join clicks and messages to find time to first action

Last updated: January 25, 2026

Quick Overview

Write a query joining clicks and impressions to produce the combined time to first action.

SentinelOne
Data Manipulation (SQL/Python)
Data Scientist
SentinelOne
January 25, 2026
Data Scientist
Onsite
Data Manipulation (SQL/Python)
Hard

28

13

1,686 solved


Write a query joining clicks and impressions to produce the combined time to first action.

This question from SentinelOne'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
  • 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
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Data cleaning and transformation
Date/time manipulation
JOIN types and when to use each
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 indexes would you create to support this query?
  • What would you do if this query needs to run every 5 minutes?
  • Can you rewrite this without using subqueries?
  • How would you handle this if the data was spread across multiple databases?
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