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Google interview notes, page 64 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·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google PM interview with a classic operations-style case question. One question, business scenario format, felt more like a consulting puzzle than a typical product interview.
  • You own a gas station and suddenly see four times the normal number of customers during peak hours. How do you investigate what's happening, diagnose the root cause, and fix it?

“I went straight to root cause analysis mode: is this a supply shock somewhere nearby, a pricing anomaly, an event driving traffic?”

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Google·Product Manager·Onsite - System Design / Architecture

May 2026
Google PM interview with a classic system design flavored question that sounds deceptively simple until you're actually in the room trying to answer it coherently.
  • Walk me through everything that happens, technically and otherwise, when you type a URL into a browser and hit Enter.

“I knew this question existed.”

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Google·Software Engineer·Onsite - System Design / Architecture

May 2026
Google SWE system design round, just one question the whole time: design a key-value store. Felt deceptively simple at first and then I realized how much was actually under the hood.
  • Design a key-value store.

“I started with the basics, single node, in-memory, then the interviewer kept pushing on durability and consistency.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google product design interview, one question about building a hangman game for airplane seatback screens. Pretty open-ended and I wasn't totally sure how deep to go on the constraints side.
  • Design a hangman game for airplane seatback screens.

“I spent too long on the game mechanics themselves and kind of forgot the context matters a lot here.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google PM interview with a product strategy question about YouTube. Pretty straightforward setup but the question itself has a lot of surface area if you're not careful about scoping.
  • How would you go about increasing the frequency of user sessions on YouTube?

“I went straight to notifications and recommendation improvements, which in hindsight was way too obvious.”

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Google·Software Engineer·Technical Phone Screen

May 2026
Google SWE interview that mixed OOD with an algorithm problem, which I wasn't fully expecting. The core question was about activity timeout detection from event logs, and the follow-ups kept coming until I was basically designing a mini distributed monitoring system.
  • Given a log of activity events (each with an activity ID, an event type of start/end/heartbeat, and a timestamp) plus a timeout threshold T, design clean data structures and classes to model this, and return all activity IDs that have timed out. An activity is timed out if it started but never received an end event or a recent enough heartbeat within T time units of its last event.
  • How would your approach change if the event log is guaranteed to arrive sorted by timestamp?
  • How would you handle this problem if the events were arriving as a continuous stream, potentially out of order, with a very large number of concurrent activities?

“I started with the algorithm and they pulled me back to the class design first, which threw me off a bit.”

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Google·Data Scientist·Onsite - Behavioral / Leadership

May 2026
Behavioral round at Google for a Data Science role, heavy on the influence-and-alignment angle. One big question that basically asked you to narrate a whole project from hypothesis to outcome, with stakeholder drama in the middle.
  • Tell me about a time you used data to drive a cross-functional decision when key stakeholders initially pushed back on your recommendation. Walk through your hypothesis, how you shaped the message for non-technical partners, how you handled the disagreement, what trade-offs you accepted, and what the measurable result was.

“This is a lot to pack into one answer and I definitely ran long the first time I practiced it.”

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Google·Software Engineer·Onsite - Coding / Algorithms

May 2026
Google SWE coding round with a board simulation problem. Not the hardest thing I've seen but the constraints trip you up if you're not careful.
  • You have a 1D board with positions that are either empty, a token, or a coin. Tokens move exactly 3 steps right per move, collect a coin on landing, and can't share a position with another token. What's the maximum number of coins you can collect?

“Took me a minute to even parse what was being asked.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Got a product sense question at Google that sounds deceptively casual but actually requires you to have a real opinion and defend it.
  • Can you name a great product that was poorly marketed?

“I went with something I thought was clever and spent way too long on the 'great product' part instead of actually diagnosing the marketing failure.”

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Google·Technical Program Manager·Onsite - Product Sense / Strategy

May 2026
Google TPM interview with one case-style question about fixing city roads. Pretty open-ended, not a lot of structure given to you upfront.
  • How would you design and execute a program to repair city roads?

“I went straight into scoping and prioritization, which felt right, but I think I skipped over stakeholder alignment too fast.”

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