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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 91–120 of 653 results

  • This prompt evaluates integer reachability and invariant reasoning via repeated additive transformations (testing number-theoretic reachability and state-space analysis) alongside resource-aware scheduling and grouping logic for minimizing completion time under type and memory constraints, and it falls under the Coding & Algorithms domain.

    AmazonSoftware EngineerCoding & 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 Compute shortest path with obstacles states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to maintain dynamic statistics in a data stream using efficient data structures to achieve logarithmic insertion and constant-time retrieval.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to manage overlapping time intervals efficiently, requiring an understanding of sorting or priority queues to track resource utilization.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to use greedy strategies combined with efficient data structures to manage resource allocation and optimize revenue based on priority-based demand.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of binary tree algorithms, recursion versus iterative traversal strategies, and competence in algorithmic analysis including time and space complexity and handling deep-recursion stack overflow when computing a tree's diameter.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's skill in data manipulation and deduplication using SQL/Python, specifically mapping hierarchical product metadata to departments and computing unique user counts without double-counting, and is categorized under Data Manipulation (SQL/Python).

    AmazonSoftware EngineerData Manipulation (SQL/Python)Technical Screen
  • This question evaluates data consolidation, currency normalization, and ranking competencies, measuring the ability to combine country-specific employee data and convert salaries into a common USD basis within the Data Manipulation (SQL/Python) domain.

    AmazonData ScientistData Manipulation (SQL/Python)Technical Screen
  • Design a repeatedly invoked robot-charging controller with strict battery thresholds, exclusive station assignments, waiting robots, and safe command retries.

    AmazonSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
  • This question tests the ability to traverse an undirected graph using graph search algorithms to identify and count disjoint subgraphs.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in relational data manipulation and set-based reasoning, assessing SQL competency such as joins, aggregation, and identifying distinct customers who purchased multiple specified products.

    AmazonBusiness Intelligence EngineerData Manipulation (SQL/Python)Onsite
  • Tests data manipulation, hash set/map aggregation, and date deduplication to identify users with repeat visits across distinct calendar days.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Count four-neighbor islands in a binary matrix and consider the connectivity state needed when rows arrive as a stream.

    AmazonSoftware EngineerCoding & 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 Count expressions reaching a target sum states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates string-processing and combinatorial counting skills, including tracking distinct-character occurrences across contiguous partitions and using frequency-based pairing logic on arrays to form equal-cost packages.

    AmazonSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates proficiency in graph traversal and grid-based connected-component detection using depth-first search on a binary m x n grid, along with algorithmic complexity analysis and techniques to avoid revisiting cells.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Count how many structurally different binary search trees can store the keys 1 through n exactly once, for n up to 19. It tests reasoning about how tree shapes decompose and counting combinatorial structures efficiently instead of building every tree.

    AmazonSoftware EngineerCoding & AlgorithmsOther
  • This question evaluates a candidate's ability to implement string transformations based on a fixed character-to-code mapping and to identify distinct results, testing competencies in encoding, string manipulation, and deduplication.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question tests the ability to detect cycles in a directed graph to determine if a set of academic courses with prerequisite constraints can be completed.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in data manipulation using pandas, including relational joins and aggregation to produce country-level summary statistics like totals and averages.

    AmazonData ScientistData Manipulation (SQL/Python)Technical Screen
  • This question evaluates proficiency in SQL-based data manipulation, covering aggregation and dispersion metrics, null handling, relational joins, and window functions for ranking customers.

    AmazonData ScientistData Manipulation (SQL/Python)Technical Screen
  • Construct one valid binary tree from unordered parent-child descriptions that identify left and right links. Reuse node identities across records, support children appearing before parents, and return the unique root.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • An Amazon behavioral question on customer focus: describe a time you went above and beyond for a customer, and a change you made that was driven by customer needs. It tests how you discover customer problems, act on them beyond expectations, and measure the impact.

    AmazonSoftware EngineerBehavioral & LeadershipOnsite
  • Debug an existing Django movie catalog API whose automated tests fail, covering URL routing, query parameter handling, queryset filters on genre, director, writer, rating and year, result ordering with tie-breakers, and HTTP 500 errors. It tests a systematic, layer-by-layer debugging process under a time limit.

    AmazonSoftware EngineerSoftware Engineering FundamentalsOnline Assessment
  • This question evaluates backend debugging, RESTful API semantics, data validation and integrity, persistence behavior, and correct HTTP status and error-response handling for watch-list movie operations.

    AmazonSoftware EngineerSoftware Engineering FundamentalsOnline Assessment
  • Given a layered bookstore search backend with planted bugs, write failing tests for substring matching, scope selection, case-insensitivity, multi-key ordering and visibility, then locate and fix every defect without changing the API contract. Tests test-first debugging across layers and query design.

    AmazonSoftware EngineerSoftware Engineering FundamentalsOnline Assessment
  • An unfamiliar Node.js car-rental backend with API documentation and failing preset tests has three independent bugs: the My Cars list shows other users' cars, newly added cars never appear, and edits vanish after a refresh. The question tests systematic debugging, ownership checks across endpoints, and confirming that writes really persist.

    AmazonSoftware EngineerSoftware Engineering FundamentalsOnline Assessment
  • Tests your ability to design and implement a sliding-window rate limiter with deduplication and state cleanup, reflecting common logic and edge-case errors encountered when debugging test-driven C++ systems.

    AmazonSoftware EngineerSoftware Engineering FundamentalsOnline Assessment
  • This problem tests your systematic troubleshooting methodology for a distributed system, focusing on narrowing down the root cause of an API request failure.

    AmazonSoftware EngineerSoftware Engineering FundamentalsTechnical Screen
  • This question evaluates a candidate's competency in feature engineering and preprocessing for mixed-type tabular data, including handling sparse counts and heavy-tailed monetary features, missingness and zero-inflation, correlated continuous measurements, model-specific scaling needs, and the design of leak-safe pipelines and validation strategies.

    AmazonData ScientistMachine LearningTechnical Screen

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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