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Google interview notes, page 179 of 215

FAANG / Big Tech

Most of these Google write-ups come from Software Engineers (1,167), then Product Managers (686) and Data Scientists (125). The most reported rounds are the product sense round (667), the technical phone screen (660), the behavioral / leadership round (252) and the onsite coding round (214).

2146 interview notes · updated Oct 2026

Google·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Google SWE coding round with a grid path-counting problem. Pretty standard dynamic programming territory but the diagonal move twist made it less obvious than I expected.
  • Given an m x n 2D matrix, how many unique paths exist from the bottom-left corner to the top-right corner if you can only move up, right, or diagonally up-right? Implement the solution and provide test cases.

“The diagonal move is what got me initially.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Product analyst interview at Google with what seemed like a classic metrics investigation prompt. One question, straightforward setup, but the depth expected underneath it was not obvious at first.
  • Engagement is flat despite new user growth. What questions would you ask and what data would you pull to investigate?

“I went straight to 'engagement per user is dropping' which is the obvious read, but I should've slowed down and questioned the metric definition first.”

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Google·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Google SWE behavioral round, one question, the whole thing was basically a deep dive into how you handle not knowing what you're supposed to be doing. Felt pretty open-ended in a way that either goes well or really doesn't.
  • Tell me about a time you worked through a situation where the requirements were unclear, ownership was fuzzy, or goals were conflicting. How did you figure out what to do, and how did you get to a concrete result?

“This one is sneakier than it looks.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview with a meaty product design question around enterprise finance automation. Single question but it had a lot of layers and I wasn't fully prepared for how deep they wanted to go on the exceptions side.
  • Design a product that automates three-way matching in a Procure-to-Pay workflow, including how the system handles exceptions.

“The exceptions piece is where I stumbled.”

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Google·Software Engineer·Onsite - Product Sense / Strategy

Jun 2026
Interviewed for a BA role at Google and got hit with a feature rollout evaluation question that felt deceptively simple but had a lot of moving parts once I started talking through it.
  • How would you decide whether a new feature should be rolled out to all users?

“I went straight to metrics and experiment results, which felt right, but I forgot to talk about segmentation early on.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google coding interview with one algorithmic problem. Short and to the point, nothing fancy.
  • Explain and solve the 3-partition problem.

“Took me a second to even remember what the 3-partition problem was.”

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Google·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Google SWE coding round, one problem about simulating piece movement on a 1D board. Pretty clean problem once you see the key insight, but I spent way too long trying to brute-force it before the right approach clicked.
  • Given two equal-length strings representing a 1D board with pieces 'R' (can only move right), 'L' (can only move left), and '_' (empty), determine if the start configuration can be transformed into the target configuration through valid moves.

“My first instinct was to simulate moves which is obviously wrong at scale.”

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Google·Software Engineer·Onsite - Product Sense / Strategy

Jun 2026
Google GTM strategy question, pretty standard for a product marketing or strategy role but I fumbled the metrics piece more than I expected.
  • How would you evaluate whether a go-to-market strategy was successful?

“I started with awareness and conversion metrics which felt right, but then the follow-up pushed me on longer-term signals and I kind of scrambled.”

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Google·Software Engineer·Onsite - System Design / Architecture

Jun 2026
System design round at Google for a software engineering role. The problem was building a surge pricing calculator, which sounds straightforward but has a lot of moving parts once you start thinking about real-time data at scale.
  • Design a system that computes surge pricing for a ride-sharing platform, where the price multiplier is derived from the ratio of active users (app opens) to available drivers in a given geographic area.

“The ratio formula itself is simple enough, but I got tripped up on the geo-bucketing part.”

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Google·Software Engineer·Online Assessment (OA)

Jun 2026
Google SWE coding problem involving grid coverage with horizontal and vertical boards. Classic minimum cover type problem, felt like an online assessment style question.
  • Given an m×n binary grid where 0s represent holes, find the minimum number of boards needed to cover all holes. Each board covers either a full row (1×n) or a full column (m×1), and can overlap intact cells.

“This is a minimum vertex cover problem on a bipartite graph, which I did not see at first.”

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