Calculate time to first action per product

Last updated: May 23, 2026

Quick Overview

Write a query to compute time to first action grouped by date, handling edge cases like nulls and duplicates.

Square/Block
Data Manipulation (SQL/Python)
Data Scientist
Square/Block
May 23, 2026
Data Scientist
Onsite
Data Manipulation (SQL/Python)
Hard

7

0

2,447 solved


Write a query to compute time to first action grouped by date, handling edge cases like nulls and duplicates.

Square/Block asks this during the Onsite 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
Aggregate functions and GROUP BY
NULL handling and COALESCE
Index optimization and query performance
Subqueries and correlated subqueries
JOIN types and when to use each
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 validate the correctness of your query results?
  • How would you optimize this query for a table with 100 million rows?
  • How would you handle slowly changing dimensions in this scenario?
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Sample Answer
Approach

Break the problem into logical steps before writing SQL. Think about: 1. What tables do I need to join and on which keys? 2. What filtering (WHERE) d...

Solution Pattern

```sql WITH filtered_data AS ( SELECT * FROM main_table WHERE condition = 'value' AND date_col >= '2024-01-01' ), aggregated AS ( SELECT ...


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