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Amazon interview questions

653 practice questions in the style of Amazon's interviews, covering Behavioral & Leadership, System Design, Coding & Algorithms, Product / Decision Making, Data Manipulation (SQL/Python), Analytics & Experimentation, Statistics & Math, Software Engineering Fundamentals, Machine Learning, ML System Design, Product Design & Strategy.

Questions653

50 easy471 medium132 hard

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Amazon interview questions by the numbers

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Katkat has 653 Amazon interview questions. The largest topics are Coding & Algorithms (35%), Behavioral & Leadership (26%) and System Design (9%). By difficulty: 8% easy, 72% medium and 20% hard. The most common round is Technical Screen (49%). Frequent concepts include System Design, Behavioral, Leadership and Algorithms.

Difficulty

  • Easy8% · 50
  • Medium72% · 471
  • Hard20% · 132

Interview rounds

  • Technical Screen49% · 318
  • Onsite37% · 243
  • Online Assessment11% · 71
  • Other2% · 13
  • HR Screen1% · 8

Roles

  • Software Engineer61% · 400
  • Data Scientist22% · 144
  • Applied Scientist8% · 54
  • Product Manager3% · 22
  • Business Intelligence Engineer2% · 13

Frequent concepts

  • System Design5% · 34
  • Behavioral5% · 32
  • Leadership4% · 29
  • Algorithms4% · 23
  • Distributed Systems4% · 23
  • Optimization3% · 21

Showing 601–630 of 653 results

  • Implement two independent tasks: identify stocked centers close enough to a graph destination and return any exact dictionary segmentation of a string. Handle disconnected routes, duplicate edges, missing inventory, repeated suffix work, and large inputs while explaining complexity.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates graph and grid traversal skills, state modeling over time, and constrained reachability combining free transit edges with Manhattan-distance walking.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates proficiency in binary search, algorithmic implementation on sorted arrays, and understanding of time complexity and index management.

    AmazonData ScientistCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to determine the minimum capacity required to complete tasks within a deadline and optimize the cost of purchasing items grouped in bundles.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This multi-part question evaluates combinatorics and permutation generation, tree traversal and node-relationship classification, and array/sequence processing under bounded-gap constraints, measuring algorithmic design, complexity reasoning, and data-structure manipulation within the Coding & Algorithms domain.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • These two problems evaluate proficiency with greedy algorithms, array manipulation, simulation of stateful processes, and feasibility analysis under capacity constraints.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This task evaluates string manipulation and encoding for generating unique Morse representations, along with sentence segmentation and combinatorial enumeration for producing all valid word-break sentences, focusing on transformation, deduplication, and decomposition skills.

    AmazonData EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of disjoint-set (union-find) operations, directed graph processing including cycle detection and ordering, contiguous subarray sum reasoning, and online streaming/anagram detection techniques, emphasizing data structures and algorithmic problem-solving.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • Describe initiative beyond assigned work with clear impact, owner coordination, bounded scope, delivery responsibility, and a sustainable handoff.

    AmazonSoftware EngineerBehavioral & LeadershipOnsite
  • This question evaluates proficiency in array and list algorithms, including ordering and counting techniques for relative element ranking, merging multiple sorted inputs, and algorithmic design for a package locker retrieval operation, testing data structure manipulation and retrieval logic.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to efficiently detect duplicates using hashing and to apply the sliding window technique to find subarrays that meet specific frequency constraints.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This two-part question evaluates algorithmic problem-solving skills: Task A focuses on combinatorial optimization and cost-based sequencing under quadratic jump costs, while Task B assesses string multiset reasoning and character-frequency manipulation to determine anagram similarity.

    AmazonSoftware EngineerCoding & AlgorithmsOnline Assessment
  • Solve median extremes and segment flips evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    AmazonSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates algorithm design and data structure proficiency, focusing on sliding-window techniques for fixed-length subarray aggregates and heap- or hashmap-based approaches for maintaining medians in a real-time integer stream, along with considerations for concurrent execution.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates algorithmic problem solving across array scanning, BFS-based constrained shortest-path selection, and interval merging, with emphasis on time/space complexity reasoning, correctness proofs, and thorough edge-case handling. It is commonly asked to assess efficiency guarantees (e.g.

    AmazonData ScientistCoding & AlgorithmsTechnical Screen
  • Solve string partition and equal-sum package problems evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    AmazonSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates algorithm design and analysis skills, including selection under sum constraints with negatives and zeros, streaming and query-preprocessing strategies for repeated budgets, and number-theoretic factor enumeration for large N, all within the Coding & Algorithms domain.

    AmazonData ScientistCoding & AlgorithmsOnline Assessment
  • This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Solve three coding tasks: binary search, tree path, subarray states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This pair of problems evaluates proficiency with tree data structures and traversal concepts (deepest shared ancestor) and with dynamic programming/state optimization on linear arrays (maximizing non-adjacent house values), assessing algorithmic reasoning, complexity awareness, and data-structure manipulation.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in data-structure manipulation (set operations, mapping and deduplication), directed-graph modeling and traversal for reachability, and algorithmic time/space complexity analysis.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This question set evaluates string-processing and algorithmic problem-solving skills, including encoding and transformation for unique representations and dynamic programming, memoization, and backtracking for enumerating all valid segmentations.

    AmazonData ScientistCoding & AlgorithmsTechnical Screen
  • This question evaluates array and hashing algorithms, pair-sum reasoning including duplicate handling and lexicographic minimality, streaming and external-memory algorithm design, trade-offs in time/space complexity, and extension to three-sum with deduplication.

    AmazonData ScientistCoding & AlgorithmsOnsite
  • Design a simplified in-memory spreadsheet supporting direct cell assignment, formula assignment (summation with potential duplicate cell references), and retrieval with dynamic dependency propagation.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • Phone screen coding problem: process push and pop operations on a stack in which every pop removes the value that currently occurs most often, breaking ties by the tied value closest to the top. It tests designing a data structure that tracks frequency and recency together efficiently.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This question assesses the candidate's ability to navigate professional disagreement, exercise intellectual humility, and maintain team cohesion while advocating for technical standards.

    AmazonSoftware EngineerBehavioral & LeadershipTechnical Screen
  • Tell about deliberately stepping outside your professional comfort zone in responsibility, domain, influence, or communication. Explain the real risk, why you accepted it, preparation and feedback, the outcome, and how the experience changed later behavior.

    AmazonSoftware EngineerBehavioral & LeadershipTechnical Screen
  • This question assesses the candidate's ability to balance individual empathy and mentorship with team productivity and project deadlines, testing their conflict resolution and leadership skills.

    AmazonSoftware EngineerBehavioral & LeadershipTechnical Screen
  • Explain customer-focused initiative through direct evidence, a validated problem, a focused change, and confirmation that the customer experience improved.

    AmazonSoftware EngineerBehavioral & LeadershipOnsite
  • This question tests your ability to identify and mitigate significant technical risks in a project while demonstrating leadership, accountability, and the ability to influence stakeholders.

    AmazonSoftware EngineerBehavioral & LeadershipTechnical Screen
  • This question evaluates competency in statistical inference and multivariate analysis, covering hypothesis formulation about equal distributions, preprocessing and normalization considerations, choice of statistical tests or modeling approaches, and interpretation of significance and effect size.

    AmazonApplied ScientistMachine LearningOnsite

Amazon interview experiences

All 396 →
  • L6 Phone Screen With an Impatient Interviewer, LCA Follow-up StuckAmazon · Software Engineer · Senior+ · Technical Screen · Oct 2026

    The interviewer was impossible to find anywhere online, I couldn't find a thing about him and I'm speechless. BQ: 1. How do you evaluate customer experience? 2. A major unexpected obstacle. For the first one, I think the point of the question was the evaluation part, and my story was just directly collecting feedback, which he wasn't happy with 😭 For the second one, he felt the obstacle wasn't ma…

  • Three Rounds of Graphs, System Design and Leadership PrinciplesAmazon · Software Engineer · Technical Screen · Oct 2026

    I interviewed with the Agentic AI security product team under AWS. The location is Austin. Every round was 1 hour. Round 1 was a DAG topological sort. It was pretty good, pretty basic. Round 2 was another directed graph problem. This team really likes graph problems. It was something like working out what you need to make a cake, and it is very similar to a LeetCode problem. Round 3 was a traditi…

  • Four Rounds with Detailed Behavioral QuestionsAmazon · Software Engineer · Onsite · Sep 2026

    The author describes four Amazon virtual-onsite interviews for an SDE2 role, each combining behavioral discussion with technical work. The technical topics were dependency ordering and selective reruns, a high-volume inventory-update service, an extensible document-search library, and merging timestamp-ordered event streams without loading everything into memory. Behavioral questions examined inv…

  • One DSA Round, Two Mediums, RejectedAmazon · Frontend Engineer · Technical Screen · Sep 2026
    Rejected

    I applied through a LinkedIn post for SDE I (Frontend). HR contacted me over a call and we discussed the further rounds. Round 1 (PS-DS Round) (1hr) Two DSA medium questions were asked, and I was able to solve both of them within the time limit (~40 mins). The interviewer was helpful and provided hints. Q1. Lowest Common Ancestor of a Binary Search Tree Q2. Ones and Zeroes Explain brute force, th…

  • Three BQ questions: Q1: Can you tell me about a time when you pushed back against a decision that negatively impacted your team? What was the issue? How did it turn out? Q2: Can you tell me about a time when a system was failing intermittently, and the very obvious metrics were all looking good? How did you find the root cause, and how long did it take? Q3: Can you tell me about a problem you had…

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