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Amazon Interview Questions (1986)

Practice real interview problems from Amazon

#2704

To Be Or Not To Be

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Adobe+5
#2706

Buy Two Chocolates

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Amazon+1
#2723

Add Two Promises

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Amazon+4
#2724

Sort By

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Amazon+2
#2769

Find the Maximum Achievable Number

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Amazon+3
#2788

Split Strings by Separator

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Amazon+2
#2798

Number of Employees Who Met the Target

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Amazon+1
#2843

Count Symmetric Integers

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Amazon+4
#2855

Minimum Right Shifts to Sort the Array

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Accenture+1
#2864

Maximum Odd Binary Number

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Amazon+2
#2873

Maximum Value of an Ordered Triplet I

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Amazon+3
#2877

Create a DataFrame from List

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Amazon+4
#2879

Display the First Three Rows

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Amazon+3
#2889

Reshape Data: Pivot

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Amazon+1
#2890

Reshape Data: Melt

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Amazon+1
#2942

Find Words Containing Character

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Amazon+5
#3000

Maximum Area of Longest Diagonal Rectangle

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Accenture+4
#3019

Number of Changing Keys

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Amazon+4
#3028

Ant on the Boundary

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Accenture+2
#3110

Score of a String

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Amazon+4
#3136

Valid Word

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Amazon+7
#3151

Special Array I

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Amazon+5
#3174

Clear Digits

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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.