Arslan Ahmad

Amazon Interview Questions: The Ultimate Preparation Guide

How to standout in Amazon's tech interview.

Getting an interview at Amazon is a major accomplishment. With thousands of applicants every year and intense competition, securing an interview slot is an achievement in itself. Now you need to put in the work to make sure you ace the interview process.

In this comprehensive guide, we will cover everything you need to know to crush your Amazon interviews, including:

  • The full breakdown of Amazon's rigorous interview process
  • How to thoroughly prepare for Amazon's behavioral and technical interviews
  • Detailed examples of the most common Amazon interview questions
  • 5 techniques to really impress your interviewers
  • Pro tips and strategies to stand out from the competition
  • Insights into Amazon's company culture and leadership principles
  • Recommended resources for practice and study

This guide will equip you with the skills, stories, and knowledge to master your Amazon interviews. Let's dive in!

Chapter 1 - Amazon's Interview Process Fully Explained

The first step to acing Amazon's interview gauntlet is understanding exactly what you will face. Let's break down what to expect in each stage of Amazon's notoriously rigorous interview process.

The Recruiter Phone Screen

Your journey starts with a recruiter phone screen, usually scheduled for 30 minutes. Here's what to expect:

  • Introductions - The recruiter will give brief background on themselves and ask you to walk through your resume and experience. Be succinct but thorough when summarizing your background.

  • Motivations - Expect questions about why you are interested in Amazon and the role you applied for. Be specific - do your research so you can speak intelligently about the team, products, and technologies involved in the position.

  • Experience - The recruiter will probe into details of your work history, especially your major technical projects and accomplishments. Be ready to talk technically about the most relevant parts of your background.

  • Leadership principles - Some recruiters may ask you to describe how experiences tie back to Amazon's leadership principles. Have these principles on the tip of your tongue and relate your background to them.

  • Questions - The recruiter will ask if you have any questions. Always have thoughtful questions ready that show your understanding of and enthusiasm for the role.

  • Next steps - If interested, the recruiter will outline next steps and timelines. This usually involves a technical phone screen.

With practice and preparation, you can ace the recruiter screen and move on to the more difficult technical interviews.

The Technical Phone Screen

If you impress the recruiter, next up is the technical phone screen, usually scheduled for 45-60 minutes. This is often your first coding/architecture interview, so bring your A game. Here's what to expect:

  • Introductions - You'll be introduced to an Amazon engineer who will conduct the technical interview. Expect them to briefly summarize their role.

  • Coding - The core of the interview will be data structure, algorithm, and language questions. Think 2-3 mediums from LeetCode. Communicate clearly and check edge cases.

  • Architecture - Expect at least one system design or object oriented design question. Get clarification, highlight tradeoffs, and explain reasoning.

  • Experience - The interviewer may ask you to expand on parts of your background relevant to the role. Keep answers clear and concise.

  • Next Steps - If you pass, next is a full day of on-site final interviews. Ask about recommended preparation.

The technical screen will evaluate both your computer science fundamentals and communication skills. Practice mock interviews extensively so you are comfortable responding confidently to a wide range of technical prompts.

The All-Day Final Interviews

If you successfully navigate the phone screens, you'll be invited to Amazon's headquarters for 4-6 back-to-back interview sessions. This is an all day affair, usually lasting 6-8 hours, including breaks between sessions.

What can you expect during these final on-site interviews?

  • Diverse interviewers - You will meet with various managers, engineers, and senior leaders from the department you are interviewing for.

  • Mix of questions - Expect behavioral, technical, and leadership principle questions across your different sessions.

  • Coding challenges - At least two of the interviews will involve writing code in a relevant language like Python or Java. Brush up on those whiteboard coding skills.

  • System design - Be ready to discuss approaches to core system design problems like scaling databases or designing highly-available services.

  • Projects and experience - Interviewers will probe into your resume, past work, side-projects, and qualifications. Be an expert on your own background.

  • Culture and principles - As an executive frontrunner, Amazon cares about culture fit. Showcase how your values align.

  • Meals - You'll have lunch with employees and get a feel for Amazon's culture. Use this time to ask good questions and learn.

The final round is intense. Thorough preparation of your stories, technical skills, and thinking is key. You want to enter the office confident and ready to tackle whatever comes your way over the course of this long day.

The Hiring Manager Review

After running through the on-site gauntlet, the final step is review by the hiring manager. The individual interviewers will submit their evaluations and commentary on your performance.

The hiring manager looks at factors like:

  • Did you pass a majority of the interview bars?
  • Do the interviewers agree you have the right skills for the role?
  • Did you stand out in any particular area?
  • Do you show mission alignment with Amazon's principles?

If the hiring manager gives the thumbs up, congratulations! Expect a call with the official job offer details. Time to celebrate.

However, it's not uncommon for candidates to get rejections at this stage due to mixed interview feedback or concerns raised over the course of the day's assessments.

If you receive a "no" from the hiring manager, you may be able to re-apply and restart the process after 6-12 months. Use the time to brush up your skills and prepare to come back stronger.

Chapter 2 - How to Thoroughly Prepare for Amazon's Behavioral and Technical Interview Questions

You landed an interview at Amazon. Awesome! But don't let up now. The real work starts here. Thorough preparation is what will set you apart. Here is a detailed guide to getting ready for Amazon's behavioral, technical and leadership focused interviews.

Preparing for the Behavioral Interview

Nail the behavioral part of your Amazon interviews by following these preparation tips:

Understand Amazon's Leadership Principles Cold

Amazon's leadership principles are 14 core values that drive their culture and guide employee behaviors. Master them inside and out:

  • Customer obsession - Earn and keep customer trust above all else. Make their problems your problems and find solutions.

  • Ownership - Take end-to-end ownership of your work. Don't settle for less than excellence.

  • Invent and simplify - Solve complex problems with simple, elegant solutions. Cut through ambiguity.

  • Are right, a lot - Make data-driven decisions, even if unpopular. Base choices on research, analysis and judgement.

  • Learn and be curious - Be inquisitive. Seek knowledge and truth in all things. Stay hungry to learn.

  • Hire and develop the best - Only keep stunning colleagues. Coach them towards excellence.

  • Insist on the highest standards - Expect only the best in quality and performance from yourself and others.

  • Think big - Create bold, game-changing ideas. Make no small plans.

  • Bias for action - Move fast. Empower teams to act without constant supervision.

  • Frugality - Accomplish more with less. Constraints breed creative solutions. Eliminate waste.

  • Earn trust - Listen closely. Treat others respectfully. Keep your word.

  • Dive deep - Invest the time to fully understand details, issues and priorities before making decisions.

  • Have backbone; disagree and commit - Challenge assumptions respectfully. Then unify behind group decisions.

  • Deliver results - Focus on key inputs and outputs. Set challenging goals and exceed them. Get the right things done.

You will be expected to tie your interview answers directly to demonstrating these principles.

Craft Stories That Showcase Leadership Principles

Practice storytelling by structuring compelling stories from your background that highlight Amazon principles like customer obsession, high standards, and bias for action.

Make your stories concise and impactful. Set the context briefly, build up the challenge, then spend time on the resolution and your actions demonstrating leadership.

Prepare for Classic Behavioral and Situational Questions

Expect Amazon behavioral questions like:

  • Tell me about a time you had a conflict at work. How did you handle it?
  • Give me an example of how you solved a difficult problem.
  • Describe a time you had to deal significant ambiguity. What did you do?

Research common behavioral and situational questions asked at Amazon. Draft stories from your background that set up challenges clearly, walk through your response, and highlight leadership principles you exhibited.

Practice Mock Interviews Extensively

Set up practice behavioral interviews with colleagues and friends. Don't memorize stories verbatim, but practice telling them clearly while highlighting Amazon values.

Get feedback on where your interview skills are strong versus areas that need polish. Refine stories to be clear, concise and impactful.

Mock interviews are the best way to build confidence for real Amazon behavioral and situational questions. Put in the practice time here.

Preparing for the Technical Interview

Amazon's technical interview will rigorously assess your programming, algorithms, system design and computer science skills. Be ready with:

Fluency in Key Data Structures and Algorithms

You need mastery of fundamental data structures like arrays, linked lists, trees, graphs, stacks and queues.

Master core algorithms including sorting, searching, recursion, breadth/depth first search, dynamic programming, and common algorithms on trees and graphs.

Spend time implementing key data structures and algorithms from scratch. Understand time and space complexities.

Practice LeetCode, HackerRank, Etc

Work through problems on LeetCode, HackerRank, and other online judges to hone your skills.

Aim to complete at least 50-100 problems across difficulty levels so you have seen a wide range of coding and algorithm challenges.

Focus especially on Amazon-frequent topics like arrays, strings, trees, graphs, hashmaps, sorting, and breadth/depth first search.

Brush Up on Core Object Oriented and System Design Concepts

Study principles like inheritance, polymorphism, encapsulation, abstraction, and design patterns.

Review system design approaches for large scale services - load balancing, databases, caching, microservices, etc.

Be able to intelligently discuss options and tradeoffs for designing complex systems like Amazon's platforms.

Do Regular Mock Technical Interviews

Set up practice technical interviews to get comfortable with formulating approaches to new problems while thinking out loud.

Ask your interviewer for detailed feedback on areas like how clearly you communicated, if you considered edge cases, and the efficiency of your solution.

Mock interviews will expose weaknesses and gaps in knowledge to focus your studying. They are instrumental to acing Amazon's technical gauntlet.

Thorough technical preparation and practice will ensure you are comfortable responding confidently to a wide range of technical interview questions.

Mastering Amazon's Leadership Principles

Given Amazon's intense focus on culture and leadership values, you need to go in with a mastery of their leadership principles. Some tips:

Know Examples That Demonstrate Each Principle

Come equipped with stories that highlight owning decisions, bias for action, customer obsession, high standards, and other Amazon values. Have vivid examples ready.

Reference the Principles in Your Responses

Weave connections to Amazon principles like "earn trust" and "are right a lot" into your interview answers. Show you embody these values.

Ask Good Questions About Culture and Principles

When given the opportunity, ask smart questions about how Amazon lives the leadership principles day-to-day. Show your interest.

Do Your Research

Study how Amazon leaders talk about the company's values. Learn from examples of employees demonstrating the principles.

Evaluate Your Own Alignment

Reflect on your own values and principles. How do they align with Amazon's culture? Highlight these synergies.

Mastering Amazon's principles will help you stand out and prove you are mission aligned with their culture. Put in the work here - it will pay dividends.

Chapter 3 - Examples of Common Amazon Interview Questions (With Detailed Answers)

Preparing for Amazon interviews is all about practice. Mastering the content is step one, but you need to hone your communication skills for succinctly responding to prompts.

Let's review some of the most common Amazon interview questions, along with detailed guidance and sample answers to each.

Examples of Common Amazon Behavioral Interview Questions

Behavioral questions are critical in Amazon's interview process. Practice crafting compelling stories that shine light on your background while demonstrating Amazon's leadership principles.

Here are some common behavioral interview questions with sample answers:

Question: Tell me about yourself and walk me through your resume.

Sample Answer: I'm a software engineer with 5 years experience building scalable cloud services...(brief summary of background). I started my career at Acme Co developing APIs in Python. We served over 50 million users so I became well versed in building secure, highly reliable systems. Next I joined Stealth Startup as an early engineer where I designed core infrastructure for their blockchain platform. I opted for a startup so I could gain experience rapidly owning large parts of the system. Most recently, I spent 2 years at Wonder Technologies focused on machine learning applications. Across these experiences, I've consistently demonstrated strengths around diving deep into complex technical problems, taking ownership of my work, insisting on high standards, and keeping the customer top of mind. I'm passionate about leveraging my background in high scale distributed systems and machine learning to help Amazon develop innovative cloud services. That's why I was so excited to apply for this role.

Key Takeaway: Succinctly summarize your background while highlighting relevant experience. Wrap with enthusiasm for Amazon's mission.

Question: Tell me about a time you had to deal with ambiguity on a project. How did you handle it?

Sample Answer: Early in my tenure as lead engineer on the platform team at Wonder Technologies, our product roadmap was very ambiguous. Requirements were vague and it was unclear how features would work. Rather than make assumptions, I scheduled time with product managers and designers to understand their vision, priorities and constraints. I asked probing questions to clarify unknowns and get insights into what success looked like for them. As options became clearer, I put together wireframes and technical proposals outlining tradeoffs so we could pick a direction. By diving deep into the details and insisting on clear requirements before charging ahead, we designed an optimal solution that made customers very happy.

Key Takeaway: Outline the uncertainty you faced, then demonstrate skills like diving deep, interacting cross-functionally, and insisting on clarity.

Question: Tell me about a time you had a conflict at work. How did you handle it?

Sample Answer: As the tech lead on a key project at Acme Co, I had a disagreement with our newest developer about the right technical approach. Rather than assert my perspective, I listened closely to understand their rationale and the assumptions underlying their idea. I asked thoughtful questions, avoiding knee-jerk reactions. To move forward, we collaboratively designed some prototypes to test our hypotheses and figure out which approach was optimal based on data. By keeping an open mind rather than pushing bias, we arrived at a superior solution. Our team learned that listening and experimenting resolves disagreements.

Key Takeaway: Show emotional intelligence and collaboration by being open, curios, and data-driven.

Question: Describe a time when you went above and beyond customer expectations. Why did you do this?

Sample Answer: When I was leading development of a new analytics feature at Wonder Technologies, I proactively reached out to some beta users to understand how they would leverage the reports. One customer detailed an unexpected use case we hadn't considered around correlating web traffic with marketing spend. I proposed building custom aggregations to support their needs, even though it was out of scope. My team worked evenings and weekends to deliver this capability because I knew it would add huge value for that customer's business if we could enable their workflow. Our efforts paid off - they expanded usage significantly after we over-delivered for them. I took the initiative driven by my focus on customer value.

Key Takeaway: Go above and beyond for customers by proactively understanding their needs and delivering solutions.

Question: Tell me about a time you had to explain a complex technical concept to people without technical backgrounds. How did you ensure understanding?

Sample Answer: As a machine learning engineer at Wonder Technologies, our CEO asked me to present our new anomaly detection algorithms to the Board. While technically knowledgable, most of the Board lacked ML expertise. I knew a dense technical presentation would miss the mark. Instead, I built an intuitive analogy using relatable concepts like social media connections to explain concepts like clustering. I kept the session interactive with Q&A time to assess understanding. Based on feedback, I refined my future explanations of our ML approach to focus on the business value delivered versus academic details. My ability to break down complex technical details accessibly helped the Board grasp how our technology differentiated us.

Key Takeaway: Demonstrate you can break down technical concepts and tailor communication for the audience's needs.

Question: Tell me about a time you failed or made a mistake at work. What did you learn from it?

Sample Answer: Early in my first software role out of college, I was tasked with speeding up our customer portal's page load times, which were suffering due to technical debt. I jumped right into overhauling our caching infrastructure without sufficient planning or testing. While well intentioned, this led to outages that impacted customers. I learned the hard way that diving deep into diagnostics, creating rollback plans, and having robust testing discipline is mandatory, especially for critical systems. This experience shaped my approach of being methodical, risk averse, and obsessive about resiliency when modifying production systems today.

Question: Tell me about a time you had to make a difficult decision with limited information. How did you approach it?

Sample Answer: As the tech lead for a new product launch at Acme Co, we faced constant ambiguity around requirements that made decisions difficult. To plan effectively, I focused the team on small milestones rather than multi-month goals. We reviewed our priorities and unknowns regularly to get everyone aligned. When struggles arose, I drove rapid prototyping and iteration to validate hypotheses and prevent wasted effort. My relentless focus on facts and data helped us course correct quickly. While not every decision was perfect due to uncertainty, this empirical approach optimized our chances of success.

Key Takeaway: Make rational decisions amidst uncertainty by focusing on data, rapid validation, and continuous alignment.

Question: Describe a time when you solved an analytically complex problem. What was your process?

Sample Answer: My team at Stealth Startup faced reliability issues with our Kubernetes cluster that made debugging tricky. Pod failures seemed random and intermittent. I studied patterns in logs but saw no obvious correlations. Rather than conjecture, I decomposed step-by-step what happens when Kubernetes schedules pods. I wrote tools to collect metrics at each stage. After analyzing the data, I discovered resource bottlenecks on specific nodes. By methodically eliminating hypotheses, I uncovered the root cause. This experience demonstrated the importance of having an analytical, patient approach rather than jumping to conclusions when solving thorny technical issues.

Key Takeaway: Demonstrate analytical rigor by collecting data, synthesizing insights, and driving to root causes.

Question: Tell me about a time you had to adapt to a colleague's working style in order to complete a project or achieve your objectives.

Sample Answer: Early in my tenure at Acme Co, I was partnered with a colleague on a key web architecture project who had a markedly different work style. He preferred rapid prototyping versus detailed planning. I tend towards thorough upfront design. To collaborate effectively, I focused our syncs on aligning on project needs and constraints first before debating technical options. When we disagreed, I'd suggest we prototype both our ideas in parallel to see what performed best. By embracing his experimental approach as complementary rather than contrary to mine, we landed on solutions that blended our perspectives. I learned to lead flexibly based on each team member's working style.

Key Takeaway: Adapt your leadership style to get the best from each person. Seek collaborative solutions.

Question: Tell me about a time when you gave a simple solution to a complex problem.

Sample Answer: As a software engineer at Stealth Startup, our automated testing setup had become convoluted with dependencies across services slowing test times. I conducted an analysis identifying redundant test jobs and unnecessary layers of abstraction that had accrued over time. My proposal was to simplify radically - consolidating workflows, eliminating pointless mocks, and focusing tests on core functionality. With this redesign, testing became extremely streamlined. This example highlighted that simplicity and elegance should be design goals even in complex domains. By cutting through convoluted legacy, we can reframe problems in terms of core needs.

Key Takeaway: Seek simple, elegant solutions to even complicated domains by focusing on root needs.

Examples of Common Amazon Technical Interview Questions

Let's review some of the most frequent technical interview questions seen at Amazon, along with approaches for structuring your responses:

Question: Design an LRU cache data structure.


  • Clarify requirements like cache size, O(1) get, key types, etc.
  • Propose HashMap and Doubly Linked List. HashMap holds keys and references to nodes in linked list
  • Put() moves new node to front of list
  • Get() moves hit node to front of list
  • When full, remove oldest node from end of linked list

Discuss complexity analysis and possible extensions like adding expiration.

Key Takeaway: Discuss data structures, logic, complexity, and extensions for implementing system requirements.

Question: Given a string, reverse the order of characters in each word within it.


  • Iterate string word by word using split()
  • For each word, iterate characters backwards and append to output list
  • Join output list into space separated string
  • Consider edge cases like punctuation, numbers, etc.

Discuss algorithm efficiency and optimizations like in place reversal.

Key Takeaway: Walk through logical steps to solve coding challenge. Analyze efficiency and handle special cases.

Question: Estimate how many gas stations are in your city.


  • Clarify assumptions needed - size of city, any known data points, etc.
  • Estimate gas stations per square mile based on sample neighborhoods
  • Calculate total square miles for city
  • Derive nationwide gas station density per capita as baseline
  • Compare densities to produce estimate of total gas stations

Discuss assumptions, sensitivity analysis, and approaches to refine estimate.

Key Takeaway: Demonstrate analytical reasoning and data-driven estimation skills. Discuss assumptions and refinements.

Question: Design a system like Twitter to handle massive tweet volume.


  • Outline core API endpoints like post tweet, get timeline, follow user, etc.
  • Propose high level architecture - application layer, caching, NoSQL database for storage
  • Discuss partitioning schemes to handle writes across shards
  • Optimize timelines for celebrities with high followers using dedicated caches
  • Scale reads via caching, replication, DB read replicas

Dive into areas like reliability, scaling pain points, and optimizations.

Key Takeaway: Provide system design covering APIs, architecture, partitioning, caching, scale and reliability.

Question: You have millions of users uploading photos. How do you store them efficiently?


  • Clarify requirements like expected user base, access patterns, and storage limitations
  • Propose distributed object storage like AWS S3 to manage large volume of unstructured data
  • Discuss challenges like managing access controls, optimizing latency, handling failures
  • Suggest optimizations like CDNs for caching, metadata DBs for queries, compression to reduce storage footprint

Emphasize scalability in discussing architecture.

Key Takeaway: Outline architecture to address scale and performance challenges prompted by question.

Question: Given a binary tree, print all root-to-leaf paths.


  • Traverse the tree recursively, maintaining path in each recursion
  • Add node to path before recursive call and remove after
  • When reach a leaf, print accumulated path
  • Handle formatting output like inserting arrows between nodes

Discuss algorithm complexity and potentially iterative solutions.

Key Takeaway: Walk through key steps in traversal algorithms and handle output formatting.

Chapter 4 - How to Stand Out: 5 Techniques to Impress Amazon Interviewers

Now that you are armed with an understanding of Amazon's interview format, leadership principles, and practice responding to sample questions - let's discuss some pro tips to stand out from the competition.

Implement these strategies to impress your Amazon interviewers and highlight why you are the ideal candidate:

1. Demonstrate Deep Passion for Customer Obsession

Customer obsession is arguably Amazon's number one cultural value. Come ready with vivid stories that demonstrate putting customer needs first.

Frame your background and experience back to examples of delighting customers, solving pain points, and building human centered products.

Ask thoughtful questions around how teams prioritize solving customer problems and gather insights.

Show you live and breathe this principle in all you do.

2. Display Leadership Maturity Beyond Your Years

Interviewers want evidence you can handle ambiguity, make sound decisions, and lead with maturity.

Demonstrate these qualities by highlighting projects or initiatives you drove end-to-end.

Discuss challenges faced pragmatically, rather than complaining or blaming external factors.

Show you can operate autonomously and make shrewd calls in the face of uncertainty.

Come across as unflappable in dealing with stress and obstacles.

3. Balance Smarts with Humility

While intellect and analytical abilities are key, arrogance is a non-starter.

Highlight your capabilities and track record for results without ego or entitlement.

Admit openly when you don't know something rather than trying to fake it.

Embrace mentoring opportunities to showcase you are continually learning.

Check any tendencies towards stubbornness or now-it-all attitudes.

4. Ask Insightful Questions

Interviews go two ways. Asking smart, researched questions impresses interviewers.

Inquire about team challenges, Amazon's future ambitions, org culture, technical architecture, etc.

Focus questions on learning more about the role problems versus just impressing.

Jot down questions as you prep so you enter interviews armed with a list.

5. Demonstrate Alignment with Mission and Values

Interviewers want to know you'll thrive within Amazon's culture.

Do your research to understand Amazon's history, principles, ambitions, and challenges.

Highlight where your skills, values, and priorities align with Amazon's mission.

Get specific on why you are so excited to bring your experience and passion to help Amazon innovate.

Check any misconceptions of Amazon or red flags that contradict their principles.

Sell why this is your dream job aligned with your long term growth.

Implementing these strategies will help you enter interviews with confidence, ace the conversations, and convince Amazon you are mission-focused talent worth investing in.

Chapter 5 - Amazon Interview Preparation Resources

Looking for additional resources to master Amazon's interview process? Here are some recommendations:


Some great books to study include:

Online Courses

Recommended online courses include:

  • Grokking the System Design Interview - Visual course on system design preparation with architecture walkthroughs and coding challenges.

  • Grokking System Design Fundamentals - Learn system design essentials required for designing scalable and high-performance systems.

  • Software Engineer Interview Unleashed - Over 21 hours of video focused exclusively on Amazon-specific software engineering interview prep.

Mock Interviews

Some options to get practice include:

  • Pramp - Free peer mock interviews where you can practice technical prompts and feedback skills.

  • - Anonymous mock interviews with senior engineers from top companies like Amazon, then get rated/reviewed.

  • LeetCode Mock Interview - Structured mock interview platform to practice solving coding challenges with shared editors and voice chat.

The best preparation comes from diligent practice through mock interviews tailored closely to Amazon's actual interview techniques and questions. Leverage these resources to refine your skills.


If you've made it this far - congratulations, you now have exhaustive preparation for nailing the Amazon interview process.

From phone screens to onsite rounds, behavioral prompts to coding challenges, leadership principles to technical architecture - we've covered it all.

You have the knowledge and tools to showcase your experience powerfully while impressing upon interviewers your alignment to Amazon's mission and culture.

Be relentlessly customer focused. Champion high standards. Apply engineering rigor and creativity. Let your passion for innovation shine through.

Keep this preparation guide handy as you practice and refine stories, coding skills, design chops, and communication style.

You are now equipped to master the Amazon interview gauntlet. Go get that offer! Your dream job awaits.

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