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Google interview notes, page 43 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·Technical Program Manager·Hiring Manager Screen

Apr 2026
TPM interview at Google with a question focused on remote project management. Pretty straightforward scenario but there's more depth to it than it looks on the surface.
  • You're leading a project entirely remotely with no in-person contact with your team. How do you keep things running smoothly?

“I jumped straight into communication cadences and async tooling, which felt right, but I forgot to talk about how you build trust without any face time.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Google PM interview with a product design question focused on internal tooling for sales teams. Pretty open-ended, which I wasn't fully ready for.
  • Design a dashboard that helps sales leaders monitor their product's performance.

“I jumped straight into metrics without clarifying who exactly 'sales leaders' meant or what decisions they'd actually be making with this thing.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Google PM interview with a product sense question about a mentor-mentee matching platform. One question, fairly open-ended, and I spent way too long on the problem framing before getting to the actual validation stuff.
  • How would you determine whether there is a real market and product fit for a mentor-mentee matching platform, and how would you go about validating an MVP?

“I started with user segmentation which felt right, but I spent too long debating who the primary user even was (mentor or mentee) before getting to any validation thinking.”

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Google·Software Engineer·Onsite - Behavioral / Leadership

Apr 2026
Behavioral round at Google for a software engineer role, just the one question about going above and beyond. Pretty standard stuff but I fumbled it more than I expected.
  • Tell me about a time you went beyond what was expected of you. What drove you to do it, and what happened as a result?

“I had a story ready but it came out kind of flat.”

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Google·Software Engineer·Onsite - Behavioral / Leadership

Apr 2026
Behavioral round at Google for an EM role, three questions, all focused on leadership instincts rather than anything technical. Pretty standard stuff but the bar felt high and they wanted real stories, not generic answers.
  • Tell me about a time you had a disagreement with a peer, manager, or partner team. How did you handle the conversation and what came out of it?
  • Describe a project where the goal or requirements were unclear. How did you move things forward and get stakeholders aligned?
  • Walk me through a time when you had more work than you could realistically handle. How did you decide what to prioritize, what to push out, and how did you communicate those trade-offs?

“I had a solid story for this but I kept second-guessing whether my resolution sounded too soft.”

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Google·Software Engineer·Technical Phone Screen

Apr 2026
Google SWE interview, got hit with an edit distance problem. Not much else to go on but it's a classic dynamic programming question so you either know it or you don't.
  • Implement a solution to compute the edit distance between two strings (minimum number of insertions, deletions, or substitutions to transform one string into another).

“Classic DP problem and I still fumbled the base case initialization for like two minutes.”

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Google·Data Scientist·Technical Phone Screen

Apr 2026
Google Data Scientist interview with a product analytics case centered on diagnosing a platform-wide drop in YouTube usage. One meaty question, very open-ended, and the kind where you can tell pretty quickly if you have a real framework or are just winging it.
  • YouTube is seeing a sudden drop in daily active users and total watch-time. How would you systematically diagnose what's going on? Walk through which metrics and funnel stages you'd look at, how you'd segment users to narrow down the problem, and what analyses or tests you'd run to confirm the root cause.

“This one felt manageable at first and then I realized halfway through my answer I was just listing metrics with no real structure.”

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Google·Software Engineer·Onsite - Behavioral / Leadership

Apr 2026
Google software engineer behavioral round, one question deep on how you handle ambiguity. Pretty standard for a big tech loop but the question has more teeth than it looks.
  • Describe a situation where you had to make meaningful progress on a hard problem even though the requirements were unclear, stakeholders were giving you conflicting signals, or you were missing key data. How did you define the problem, scope it down, and ultimately push to a decision?

“This one tripped me up more than I expected.”

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Google·Business Analyst·Onsite - Product Sense / Strategy

Apr 2026
Google interview with a market sizing question about the US paint industry. Pretty standard case-style prompt but I fumbled the structure more than I'd like to admit.
  • How would you estimate the size of the paint market in the US?

“I went bottom-up, starting with households and trying to work out how often people repaint and how much paint a room takes.”

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Google·Software Engineer·Onsite - Behavioral / Leadership

Apr 2026
Behavioral round at Google for a software engineer role. Two questions, both the kind you've seen a hundred times but still somehow manage to fumble when it counts.
  • Describe a situation where you helped a teammate who was struggling with their performance.
  • Walk me through the most technically or organizationally challenging project you've been a part of.

“I had a story ready for this but halfway through I realized I was making myself sound like the hero and my teammate sound incompetent.”

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