Amazon Data Engineer Interview Questions (2026)

Landing a Data Engineer role at Amazon requires targeted preparation. Amazon uses a structured interview process called the Bar Raiser loop. Each interviewer is assigned specific Leadership Principles to evaluate. Expect deep behavioral questions using the STAR method, combined with technical assessments relevant to the role. The Bar Raiser interviewer ensures hiring standards remain high across the company. This guide covers the most frequently asked questions and insider tips to help you succeed in your Amazon Data Engineer interview.

About the Amazon Interview Process

Amazon evaluates candidates heavily against their 16 Leadership Principles, making behavioral questions a critical part of every interview loop.

Amazon uses a structured interview process called the Bar Raiser loop. Each interviewer is assigned specific Leadership Principles to evaluate. Expect deep behavioral questions using the STAR method, combined with technical assessments relevant to the role. The Bar Raiser interviewer ensures hiring standards remain high across the company.

Why Amazon Data Engineer Interviews Are Different

Amazon Data Engineer interviews differ from standard Data Engineer interviews in several key ways. The company has a unique interview culture, specific evaluation criteria, and expects candidates to demonstrate alignment with their values and mission. Understanding these differences gives you a significant advantage over other candidates.

Top 10 Data Engineer Interview Questions at Amazon

1. Expect this at Amazon: Explain the difference between ETL and ELT.
2. Amazon candidates should prepare for: How would you design a data pipeline for real-time analytics?
3. At Amazon, you might be asked: What is the difference between a data lake and a data warehouse?
4. Amazon interviewers often ask: Describe your experience with Apache Spark or similar frameworks.
5. Expect this at Amazon: How do you handle data quality and validation?
6. Expect this at Amazon: What is data partitioning and why is it important?
7. Amazon candidates should prepare for: How do you optimize query performance on large datasets?
8. Amazon interviewers often ask: Describe a complex data pipeline you have built.
9. A common Amazon interview question: How do you handle schema evolution in data pipelines?
10. Amazon interviewers often ask: What tools do you use for data orchestration?

Amazon-Specific Preparation Tips for Data Engineer Candidates

• Memorize and prepare stories for all 16 Amazon Leadership Principles
• Use the STAR method rigorously with specific metrics and outcomes
• Prepare multiple stories for Customer Obsession and Ownership principles
• Practice system design for scalable distributed services
• Be ready to discuss trade-offs and how you handle ambiguity and conflict

General Data Engineer Interview Tips

• Be proficient in SQL and at least one programming language
• Understand distributed computing concepts
• Know common data modeling techniques
• Be ready to discuss data governance and compliance

Preparation Timeline for Amazon Data Engineer Interviews

• 4 weeks before: Research Amazon culture, recent news, and the specific team you are applying to.
• 2-3 weeks before: Practice technical questions daily and prepare behavioral stories using the STAR method.
• 1 week before: Do full mock interviews with HireFlow AI simulating Amazon interview style.
• Day before: Review your notes, prepare questions for the interviewer, and get a good night of rest.

Practice Amazon Data Engineer Interview with HireFlow AI — our AI adapts to Amazon's interview style and gives real-time feedback.