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Google Interview Questions (2322)

Practice real interview problems from Google

#1

Two Sum

Easy✓ Solution📹 Video
Accenture+126
#9

Palindrome Number

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Accenture+31
#13

Roman to Integer

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Accenture+35
#14

Longest Common Prefix

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Accenture+59
#20

Valid Parentheses

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Accenture+112
#21

Merge Two Sorted Lists

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Accenture+35
#27

Remove Element

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Adobe+9
#35

Search Insert Position

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Accenture+11
#58

Length of Last Word

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Amazon+6
#66

Plus One

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Accenture+12
#69

Sqrt(x)

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Amazon+16
#70

Climbing Stairs

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Accenture+36
#83

Remove Duplicates from Sorted List

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Amazon+8
#88

Merge Sorted Array

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Accenture+36
#118

Pascal's Triangle

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Accenture+16
#141

Linked List Cycle

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Accenture+23
#163Premium

Missing Ranges

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Google+1
#169

Majority Element

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Accenture+22
#171

Excel Sheet Column Number

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Amazon+8
#175

Combine Two Tables

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Amazon+7
#181

Employees Earning More Than Their Managers

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Accenture+9
#182

Duplicate Emails

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Amazon+6
#183

Customers Who Never Order

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Amazon+5
#193

Valid Phone Numbers

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Amazon+3
#195

Tenth Line

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Adobe+3
#196

Delete Duplicate Emails

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Amazon+8
#197

Rising Temperature

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Accenture+11
#202

Happy Number

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Accenture+26
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About Google Coding Interviews

Google’s engineering interviews are designed to test deep problem-solving ability, strong data structure knowledge, and the ability to reason through complex algorithms. Candidates are expected to write clean, efficient code while explaining their thought process clearly. Unlike some companies that emphasize memorized patterns, Google focuses on understanding fundamentals and adapting them to new problems.

The typical Google coding interview evaluates candidates on core computer science topics such as arrays, graphs, dynamic programming, trees, and advanced algorithmic thinking. Interviewers often start with a straightforward problem and progressively add constraints or follow-up variations to test how well you optimize solutions. Communication, clarity, and reasoning are just as important as the final code.

Across our dataset of 2214 real Google interview questions, several patterns appear frequently:

  • Graph traversal problems (BFS, DFS, shortest paths)
  • Dynamic programming and optimization problems
  • Tree and binary search tree manipulation
  • Advanced string and hashing problems
  • Greedy algorithms and interval problems

Google interview questions often range from medium to hard difficulty, with many requiring careful edge-case handling and time-space tradeoff analysis.

FleetCode helps you prepare efficiently by organizing real Google coding interview questions by difficulty, topic, and interview frequency. Instead of solving random problems, you can focus on patterns that actually appear in Google interviews. Each problem includes optimized solutions in Python, Java, and C++, allowing you to build the skills needed to succeed in phone screens and onsite technical rounds.

Interview Tips for Google

The Google interview process typically consists of multiple stages designed to evaluate both technical depth and problem-solving clarity. While the exact process can vary by role and location, most software engineering candidates go through the following steps.

  • Recruiter screen: A short conversation about your background, experience, and role expectations.
  • Technical phone screen (1–2 rounds): 45–60 minute coding interviews conducted in a shared editor. You will solve algorithmic problems while explaining your reasoning.
  • Onsite or virtual onsite (3–5 rounds): Multiple coding interviews plus a possible system design round for experienced candidates.
  • Hiring committee review: Interview feedback is reviewed independently before a final decision.

Common Google coding interview topics include:

  • Graphs and BFS/DFS traversal
  • Dynamic programming and recursion
  • Binary trees and tree traversal
  • Hash maps and string manipulation
  • Binary search and optimization techniques
  • Greedy algorithms and interval scheduling

Google interviewers care deeply about how you think. Always start by clarifying the problem, discussing brute-force ideas, and then improving the solution step by step. Writing perfect code immediately is less important than demonstrating structured reasoning.

Common mistakes candidates make:

  • Jumping straight into coding without discussing approach
  • Ignoring edge cases such as empty inputs or duplicates
  • Not analyzing time and space complexity
  • Failing to test the solution with sample inputs

A strong preparation strategy is to practice problems by pattern. Many successful candidates solve 200–400 high-quality DSA problems focusing on graphs, trees, and dynamic programming. Allocate about 8–12 weeks of consistent preparation, practicing daily and reviewing optimized solutions.

Using FleetCode’s curated list of 2214 Google interview questions, you can focus on problems that have actually appeared in interviews and systematically master the patterns Google evaluates most often.