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Describe a challenging project where you optimized a complex ETL process.

SQLhard0.5 min readPremium
Frequency
Low
Asked at 1 company
Category
487
questions in SQL
Difficulty Split
130E|271M|86H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Goldman Sachs
Key Concepts Tested
etljoinoptimizationpartitionspark
Expert AnswerPremium
104 wordsInterview-ready
**Situation**: Daily ETL processing 50M+ rows took 6+ hours, blocking downstream reports and risking SLA. **Task**: Reduce runtime to under 1 hour while maintaining data quality. **Action**: (1) Profiled with Spark UI and query plans; identified full-table scans and unnecessary shuffles. (2) Partitioned source by date; enabled partition pruning. (3) Replaced cross-joins with broadcast joins for small dimensions. (4) Implemented incremental processing using watermark columns....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Goldman Sachs. The answer also includes follow-up discussion points that interviewers commonly explore.

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