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Amazon Interview Questions (1986)

Practice real interview problems from Amazon

#989

Add to Array-Form of Integer

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Amazon+3
#997

Find the Town Judge

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Amazon+6
#1002

Find Common Characters

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Amazon+5
#1009

Complement of Base 10 Integer

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Amazon+4
#1046

Last Stone Weight

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Amazon+12
#1051

Height Checker

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Amazon+5
#1068

Product Sales Analysis I

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Amazon+6
#1069Premium

Product Sales Analysis II

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Amazon
#1071

Greatest Common Divisor of Strings

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Amazon+6
#1075

Project Employees I

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Amazon+5
#1082Premium

Sales Analysis I

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Amazon
#1083Premium

Sales Analysis II

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Amazon
#1084

Sales Analysis III

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Amazon+2
#1108

Defanging an IP Address

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Amazon+6
#1118Premium

Number of Days in a Month

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Amazon
#1119Premium

Remove Vowels from a String

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Amazon
#1134Premium

Armstrong Number

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Amazon
#1141

User Activity for the Past 30 Days I

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Amazon+5
#1148

Article Views I

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Accenture+8
#1179

Reformat Department Table

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Amazon+3
#1200

Minimum Absolute Difference

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Agoda+15
#1207

Unique Number of Occurrences

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Amazon+4
#1211

Queries Quality and Percentage

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Amazon+4
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About Amazon Coding Interviews

Amazon’s engineering interviews are known for combining strong data structure fundamentals with real-world problem solving. Candidates are expected to write clean, efficient code while also demonstrating Amazon’s Leadership Principles such as ownership, customer obsession, and bias for action. Whether you’re applying for an SDE internship, SDE I, or experienced role, the coding bar is consistently high.

The typical Amazon coding interview process starts with an online assessment or recruiter screen, followed by a technical phone interview and then a multi-round onsite or virtual onsite loop. In these rounds, interviewers focus heavily on data structures and algorithms while evaluating how clearly you communicate your approach and reason about trade-offs.

Across real Amazon interviews, several DSA patterns appear frequently:

  • Arrays and hashing for efficient lookups and frequency tracking
  • Trees and binary search trees, especially traversal and recursion
  • Graph problems such as BFS/DFS and shortest path variations
  • Dynamic programming for optimization problems
  • Sliding window and two-pointer techniques for array and string problems

In our dataset of 1937 Amazon interview questions, most problems fall in the medium difficulty range, with a smaller but important portion of hard problems that test optimization and deeper algorithmic thinking.

FleetCode helps you prepare the way top candidates do. Instead of random practice, you can train using real Amazon interview questions categorized by topic and difficulty. Each problem includes clear explanations and solutions in Python, Java, and C++, helping you build pattern recognition and speed before the actual interview.

Interview Tips for Amazon

Understanding Amazon’s interview structure is key to preparing effectively. Most candidates go through 4–5 stages, though the exact format can vary by role and location.

  • Online Assessment (OA): Usually 1–2 coding problems plus debugging or work-style questions. Expect medium-level array, string, or hashing problems.
  • Technical Phone Screen: A 45–60 minute interview with one coding problem solved in a shared editor. Interviewers expect a clear explanation before coding.
  • Virtual Onsite / Loop: Typically 4–5 rounds, each about 45–60 minutes. Most rounds include a coding problem and behavioral questions tied to Amazon’s Leadership Principles.
  • System Design (for experienced roles): One round may focus on designing scalable services or APIs.

The most common problem categories in Amazon interviews include:

  • Arrays, strings, and hashing
  • Binary trees and tree traversal
  • Graphs with BFS or DFS
  • Sliding window and two pointers
  • Heap and priority queue problems
  • Dynamic programming for optimization tasks

Preparation strategy that works well for Amazon:

  • Start with array, string, and hashing patterns since they appear in many online assessments.
  • Practice tree and graph traversal problems until you can implement DFS and BFS from memory.
  • Focus on writing clean code with clear variable names and edge case handling.
  • Always explain your approach before coding and discuss time and space complexity.

Common mistakes candidates make:

  • Jumping straight into coding without clarifying the problem.
  • Ignoring edge cases like empty input or duplicates.
  • Not optimizing an initial brute-force solution.
  • Forgetting to connect behavioral answers to Amazon’s Leadership Principles.

A realistic preparation timeline is 6–10 weeks. Aim to solve 150–300 targeted problems, focusing on patterns rather than sheer quantity. Practicing real Amazon interview questions—like the 1937 problems on FleetCode—helps you recognize recurring patterns and build confidence before the interview loop.