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Netflix·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Netflix data analyst interview, technical screen focused on SQL. One question, pretty deep, they wanted you to actually walk through your reasoning rather than just name-drop concepts.

Questions Asked (1)

Q1

What's the most complex SQL query you've written? Walk me through what it did, the key concepts involved, and the types of joins you used.

Data ModelingProduct Analytics & Metrics
Author's notes

I picked a query I'd written for a funnel analysis and started explaining it, but I fumbled the join explanation partway through.

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AI HintsAI Generated

Suggested Approach

Select a genuinely complex query you've written, ideally involving multiple joins, subqueries, window functions, or CTEs. Structure your answer by first stating the business problem, then walking through the query's logic step-by-step, highlighting the key SQL concepts and join types used. Emphasize the impact and any optimizations you made.

Pro tip: Quantify the impact: mention how the query improved a metric (e.g., reduced runtime from hours to minutes, enabled a new analysis) to show you understand the business value, not just the technical details.

1. Set the context

Briefly describe the business problem or analytical question the query addressed, and why it was complex (e.g., data volume, multiple sources, intricate logic).

2. Outline the query structure

Give a high-level overview of the query's components: CTEs, subqueries, main SELECT, and any window functions or aggregations.

3. Explain the joins

Detail the join types used (INNER, LEFT, FULL OUTER, etc.), why each was chosen, and how they combined data from different tables.

4. Highlight key SQL concepts

Discuss advanced concepts like window functions, recursive CTEs, pivoting, or performance tuning (indexes, query plans) that were crucial.

5. Share the outcome and learnings

Describe the query's impact (e.g., performance, insights) and any lessons learned or optimizations applied.

Key Points to Mention

  • Use of multiple join types (e.g., INNER, LEFT, FULL OUTER) and the rationale for each
  • Window functions (e.g., ROW_NUMBER, RANK, SUM OVER) for ranking or running totals
  • Common Table Expressions (CTEs) for readability and modularity
  • Subqueries or correlated subqueries for complex filtering or aggregation
  • Performance considerations: indexing, query plan analysis, and optimization techniques
  • Business impact: how the query enabled better decision-making or improved a metric

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.