Window function: lead/lag over date

Last updated: October 6, 2025

Quick Overview

Use window functions to compute rank partitioned by user_id.

Oracle
Data Manipulation (SQL/Python)
Data Scientist
Oracle
October 6, 2025
Data Scientist
Phone Screen
Data Manipulation (SQL/Python)
Medium

50

12

3,094 solved


Use window functions to compute rank partitioned by user_id.

Oracle asks this during the Phone Screen 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
  • 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
Date/time manipulation
Common Table Expressions (CTEs)
Data cleaning and transformation
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
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 would you do if this query needs to run every 5 minutes?
  • How would you optimize this query for a table with 100 million rows?
  • How would you validate the correctness of your query results?
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