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Google interview notes, page 67 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 - System Design / Architecture

May 2026
Google SWE system design round. One question, pretty open-ended, and I spent way too long on the parking layout before realizing they cared more about the payment flow.
  • Design a reservation and payment system for a parking garage.

“I jumped straight into the physical stuff, like how many floors, spot types, sensors.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google PM interview with a single product design question about building a camera for Instagram users. Pretty open-ended, which sounds fun until you're actually sitting there trying to figure out where to start.
  • How would you design a camera product tailored specifically for Instagram users?

“I went straight to user segmentation and probably spent too long on it.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google PM interview with a hardware product strategy question that was equal parts exciting and stressful. Not a lot of context to work with from the original, but the question itself is a meaty one.
  • You are a PM at Google. What is the next hardware product you would launch, and how would you price it?

“This is the kind of question where you can go a dozen different directions and none of them feel obviously right.”

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Google·Business Analyst·Technical Phone Screen

May 2026
Got a classic estimation question at Google, the kind where you have to just start talking and hope the structure comes together mid-answer.
  • Estimate the number of trains operating in the NYC subway at any given time.

“I started with total track miles, which felt like the right anchor, then tried to work backwards through headways and average train length.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Product strategy question for a PM role at Google, focused on competitive response for Gmail. Pretty classic case-style prompt but it has some teeth if you're not used to thinking through pricing dynamics.
  • You're the PM for Gmail and a competitor launches a similar email product with a $5/month subscription fee. How do you assess the situation and what do you recommend to your team?

“I went straight to 'ignore them, Gmail is free' which felt obvious but also kind of lazy in retrospect.”

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Google·Software Engineer·Technical Phone Screen

May 2026
Got a tree problem at Google for a SWE role. One question, classic graph stuff but the distance sum angle made it less obvious than it looked.
  • Given a tree with N nodes (0 to N-1) and N-1 undirected edges, compute the sum of distances from each node to every other node. Return an array where the ith element is the total distance from node i.

“My first instinct was brute force BFS from every node, which is O(N^2) and works for small inputs but N can be 3*10^4 so that's not going to cut it.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google PM interview with a big open-ended product design question about emergency response for the Tokyo Olympics. No fluff, just thrown straight into a massive ambiguous scenario with millions of users and real stakes.
  • How would you design a product to handle emergency response during the Tokyo 2020 Olympics, given the massive influx of international visitors?

“My first instinct was to jump straight into features and I had to stop myself.”

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Google·Machine Learning Engineer·Onsite - System Design / Architecture

May 2026
Google system design round, one big question about predicting Netflix watch times. Not a lot of context given upfront and I probably spent too long on the ML side when they clearly wanted to talk infrastructure.
  • Design a system to predict Netflix watch times.

“I started with data collection and feature engineering, which felt natural, but about 15 minutes in I realized I hadn't touched on serving latency or how predictions would actually get surfaced to users in real time.”

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Google·DevOps Engineer·Technical Phone Screen

May 2026
Google SRE round 1 coding interview, focused on string manipulation with evolving requirements rather than heavy algorithmic theory. Clean code and edge case handling seemed to matter more than anything clever.
  • Implement a string substitution function that replaces placeholder tokens in a string using a key-value map, similar to how environment variables work in a shell.

“Seems straightforward until you start thinking about what happens with missing keys, nested placeholders, or malformed delimiters.”

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Google·Software Engineer·Onsite - Coding / Algorithms

May 2026
Google SWE coding round, one problem the whole time: parse and evaluate nested arithmetic expressions written in function-call syntax. Seemed manageable at first but the follow-up about variable-length arguments is where things got interesting.
  • Parse and evaluate a nested function-style arithmetic expression string like add(2, mul(3, pow(4, 5))) and return the numeric result. Expressions can be arbitrarily deeply nested.
  • Follow-up: extend your solution to support variable-length argument lists, e.g. add(1, 2, 3, mul(4, 5, 6)) instead of assuming exactly two arguments per operator.

“My first instinct was to try some kind of stack-based iterative approach and I spent probably five minutes going down that road before realizing I kept getting off-by-one errors on the parenthesis tracking.”

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