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Google interview notes, page 95 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 - Behavioral / Leadership

May 2026
Behavioral round at Google for a software engineering role. Five questions, all situational, nothing technical. The focus was clearly on how you handle people and messy environments more than anything else.
  • What do you do if a teammate takes credit for work you did?
  • Tell me about a time you had to work with someone who was difficult to get along with.
  • Describe a situation where you had to juggle multiple projects or priorities at the same time.
  • How do you handle a request or set of requirements that seem unreasonable or don't make sense?
  • How would you operate on a team with poor culture, low trust, or weak processes?

“Tricky one because you can't just say 'I confronted them' without sounding combative, but you also can't say nothing or you look like a pushover.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google interview, one question about estimating SMS volume in the US. Pretty classic market sizing, nothing fancy, but I fumbled the structure more than I expected.
  • How many SMS messages are sent in the United States every day?

“I went straight to population size and tried to build up from there, which was fine, but I kept second-guessing my assumptions out loud and it made the whole thing feel shaky.”

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Google·Software Engineer·Technical Phone Screen

May 2026
Interviewed for a data analyst role at Google, got hit with a market sizing question about driverless cars. Pretty standard case-style prompt but the specific year framing threw me a little.
  • What is the market size for driverless cars in 2025?

“I started with total number of cars sold globally, then tried to estimate what fraction might be autonomous by 2025.”

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Google·Data Scientist·Technical Phone Screen

May 2026
Google data/stats interview, one meaty question about regression diagnostics that covered a lot of ground at once. Felt like a theory check more than a practical problem, which threw me a bit.
  • How do R-squared, multicollinearity, and statistical tests like the T-test and F-test help you evaluate a linear regression model and make sense of its results?

“This was a lot packed into one question and I kind of answered it in a scattered order.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Product sense question from what looked like a Google interview, focused on estimation and operational data for ride-hailing. Short question but the depth expected was real.
  • Beyond what Google Maps already provides, what are the top three variables you'd use to estimate pickup ETA for a ride-hailing service like Uber?

“I went straight to driver supply density in the area, which felt obvious in retrospect.”

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Google·Software Engineer·Onsite - Coding / Algorithms

May 2026
Google SWE coding round, basically one problem but they squeezed two versions of it out of me. The static grid version was fine, the streaming follow-up is where things got real.
  • Given a binary grid, count the number of islands where connectivity is 4-directional (up, down, left, right).
  • Now imagine land cells arrive one at a time in a stream. After each addition, return the current island count.

“I went with DFS immediately and it was fine.”

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Google·Software Engineer·Technical Phone Screen

May 2026
Google SWE interview that came down to a hit counter design problem. Not the hardest thing in the world but the follow-up on complexity analysis took more time than I expected.
  • Design a hit counter class with a hit(timestamp) method and a getHits(timestamp) method that returns the number of hits recorded in the last 300 seconds.

“Started with a queue of timestamps, which works fine but I fumbled explaining the space complexity when hits pile up.”

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Google·Software Engineer·Technical Phone Screen

May 2026
Google data science interview with a PM asking a statistics/distribution question about search behavior. Pretty short interaction from what I remember, but the question had more depth to it than I expected.
  • How would you describe the distribution of daily search queries per user?

“I started talking about a right-skewed distribution pretty quickly, which felt right, but then I kind of stumbled when thinking about how to actually characterize it precisely.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Got a product design question for a Google PM role, pretty open-ended stuff about reimagining a physical product through a tech lens. One question, no frills.
  • If Google were to enter the elevator industry, how would you design a next-generation elevator?

“I went straight to user pain points which felt right but I spent way too long on the obvious stuff like wait times and accessibility.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google PM interview with a classic product sense question about redesigning the DMV experience. Nothing too wild but it's the kind of open-ended thing that can go sideways fast if you don't anchor yourself early.
  • How would you improve the experience at a DMV?

“I started rambling about wait times before I even defined who I was designing for.”

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