These questions are based on real interview experiences from candidates who interviewed at this company. You can practice answering them interactively on Dataford to better prepare for your interview.

Preparation for Amazon is distinct from other tech giants because of the heavy emphasis on cultural alignment alongside technical skill. You must treat the behavioral component with the same rigor as the coding component.

You will be evaluated on the following key criteria:

Technical Proficiency & Coding While QAEs are not Software Development Engineers (SDEs), you are expected to read and write code. Interviewers will assess your ability to write scripts (typically in Java or Python), automate test cases, and solve algorithmic problems that demonstrate logical thinking. You must show you can build tools to test software, not just test it manually.

Test Strategy & Planning This is your core competency. You will be evaluated on your ability to take an ambiguous feature request and break it down into a comprehensive test plan. This includes defining scope, identifying edge cases, selecting the right tools, and balancing manual versus automated testing efforts.

Amazon Leadership Principles (LPs) This is the most critical non-technical filter. Amazon relies on its 14 (now 16) Leadership Principles to make hiring decisions. You will be tested on how you have demonstrated principles like Customer Obsession, Ownership, Dive Deep, and Deliver Results in your past work.

Communication & Risk Management You must demonstrate the backbone to delay a release if quality standards are not met. Interviewers look for candidates who can clearly articulate risks to stakeholders and negotiate solutions without compromising the customer experience.

The interview process for a QA Engineer at Amazon is rigorous, standardized, and data-driven. Based on recent candidate experiences, the process typically moves from an initial screening to a comprehensive onsite loop. Amazon’s philosophy is to "raise the bar" with every hire, meaning you are evaluated not just against the job description, but against the average performance of current employees in that role.

Expect a process that balances technical screening with deep behavioral behavioral inquiries. Initial rounds often focus on basic coding and testing fundamentals to ensure you meet the technical baseline. As you progress, the intensity increases. The final "Loop" consists of back-to-back interviews where different interviewers are assigned specific Leadership Principles and technical competencies to vet. This structure ensures a holistic view of your candidacy, preventing any single interviewer's bias from dominating the decision.

A unique aspect of Amazon's process is the "Bar Raiser"—an interviewer from a different team brought in to ensure the candidate is better than 50% of the current workforce in that role. They have significant veto power and focus heavily on long-term potential and culture fit.

This timeline illustrates the typical progression from application to offer. Note that the Onsite Loop is the most grueling stage, usually consisting of 4–5 separate interviews in a single day (or split over two days). Use this visual to plan your energy; ensure you have your "stories" for the Leadership Principles polished before you reach the final stage.

To succeed, you must prepare for specific evaluation "buckets." Based on recent interview data, Amazon QAE interviews fluctuate between coding-heavy and process-heavy depending on the specific team (e.g., Devices vs. AWS vs. Retail).

Test Planning & Methodologies

This is the "bread and butter" of the interview. You will be given a hypothetical scenario (e.g., "How would you test a vending machine?" or "How would you test the login page for Prime Video?") and asked to construct a strategy.

• Functional Testing: Boundary value analysis, equivalence partitioning, and handling edge cases.
• Non-Functional Testing: Performance, load, security, and accessibility testing.
• Automation Strategy: Deciding what to automate vs. what to test manually, and selecting the right framework (e.g., Selenium, Appium).
• Scenario Generation: creating test cases from ambiguous requirements.

Example questions or scenarios:

• "Design a test plan for an elevator system."
• "How would you test the 'Buy Now' button on the Amazon mobile app?"
• "What are your criteria for signing off on a release?"

Coding & Algorithms

Recent reports indicate a variance in difficulty, ranging from easy scripting to LeetCode Medium challenges. You generally do not need to produce production-grade application code, but you must write clean, executable logic.

• Data Structures: Arrays, Strings, HashMaps/Dictionaries, and Lists.
• Algorithms: String manipulation, basic sorting, and iteration logic.
• Scripting: Writing utilities to parse logs or generate test data.

Example questions or scenarios:

• "Write a function to check if a string is a palindrome."
• "Find the first non-repeating character in a string."
• "Given an array of integers, move all zeros to the end."

Leadership Principles (Behavioral)

You cannot "wing" this section. Interviewers will drill down into your answers using the STAR method (Situation, Task, Action, Result). They will ask follow-up questions to ensure you—not your team—were the driver of the success.

• Customer Obsession: Times you went above and beyond for a user.
• Bias for Action: Times you moved quickly without perfect information.
• Have Backbone; Disagree and Commit: Times you challenged a manager or developer on a quality issue.

Example questions or scenarios:

• "Tell me about a time you missed a deadline. How did you handle it?"
• "Describe a time you had to make a decision with incomplete data."
• "Tell me about a time you simplified a complex process."

As a QA Engineer at Amazon, your daily work revolves around embedding quality into the software development lifecycle. You are expected to move beyond simple "testing" and into "quality engineering."

You will own the creation and execution of detailed test plans, test cases, and test scripts. This involves working closely with Product Managers to understand requirements and with Software Development Engineers (SDEs) to understand the architecture. You will be responsible for setting up and maintaining test environments and test data, ensuring that your testing mirrors production as closely as possible.

Automation is a significant part of the role. You will build and maintain automated test suites (UI and API levels) to reduce manual overhead and accelerate release velocity. When bugs are found, you don't just report them; you perform root cause analysis, help developers reproduce them, and verify the fixes. You will also participate in design reviews to flag potential quality issues before a single line of code is written.