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Accenture Data Engineer Interview Questions & Answers (2026)
Practice the 33 most asked data engineering questions at Accenture. Covers SQL, Spark/Big Data, Behavioral and more.
Why Accenture Tests These Questions
Accenture is known for rigorous data engineering interviews that focus on practical, production-level knowledge. With 33 questions in our vault, the most common category is SQL (12 questions).
Difficulty breakdown: 9 easy, 15 medium, 9 hard. Expect system design and optimization questions at senior levels.
Top 5 Most Asked Questions at Accenture
- **Q1**: Write an SQL query to find the second-highest salary from an employee table.
- **Q2**: What is the difference between cache() and persist() in Spark? When would you use each?
- **Q3**: What is the difference between groupByKey and reduceByKey in Spark?
- **Q4**: Discuss differences between ROW_NUMBER(), RANK(), and DENSE_RANK(), and provide examples from your projects.
- **Q5**: Briefly introduce yourself and walk us through your journey as a Data Engineer so far.
Category Breakdown for Accenture Interviews
- **SQL**: 12 questions
- **Spark/Big Data**: 8 questions
- **Behavioral**: 8 questions
- **Cloud/Tools**: 4 questions
- **Python/Coding**: 1 questions
How to Prepare
Focus on SQL questions first, as they dominate Accenture's interview pattern. Practice the top-frequency questions below, then move to adjacent categories. For senior roles, expect 1-2 system design rounds.
Practice These Questions
mediumWrite an SQL query to find the second-highest salary from an employee table.→mediumWhat is the difference between cache() and persist() in Spark? When would you use each?→mediumWhat is the difference between groupByKey and reduceByKey in Spark?→mediumDiscuss differences between ROW_NUMBER(), RANK(), and DENSE_RANK(), and provide examples from your projects.→hardBriefly introduce yourself and walk us through your journey as a Data Engineer so far.→
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