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Google interview notes, page 162 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·Data Scientist·Technical Phone Screen

Jun 2026
Trust & Safety SQL case for a Data Scientist role at Google. Two heavy analytical tasks back to back, both in BigQuery, both with a pile of edge cases baked in. The kind of interview where you really feel the gap between knowing SQL and knowing it well enough to get every boundary condition right under pressure.
  • You're given a Trust & Safety schema in BigQuery with users, events, content, and moderation decisions. Define a 7-day confirmed violation rate per 1,000 active users, broken down by country, and write a single BigQuery SQL query to compute it. Be explicit about how you handle country attribution, which decisions count, late-arriving decisions, and the exact time window boundaries.
  • Using the same schema, compute 28-day auto-flag precision by rule_id. Deduplicate flags to the earliest per (content_id, rule_id) pair, then define a true positive as a violation decision that lands within 48 hours after the flag time. Write a single BigQuery SQL query.

“The country attribution piece is where I nearly tripped.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE interview with a geometry/algorithm problem that sounds deceptively clean but has a few layers to it. The double binary search approach is the key insight and I'm not sure I would've landed on it cleanly under pressure.
  • You're given a cake represented as a sequence of segments, each with an associated area. Find a straight cut that divides the total area exactly in half.

“The problem looks like a math puzzle at first and I probably would've spent too long trying to derive some closed-form formula.”

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Google·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Google SWE interview, algorithmic round focused on interval scheduling with a server capacity twist. The problem had a few layers that made it trickier than a standard meeting rooms question, and the follow-up pushed into system design territory.
  • You have a cluster of servers running daily jobs. Given a list of job intervals for a single day, where each interval has a job ID, start time, and end time, compute the minimum number of servers needed. The catch: multiple intervals sharing the same job ID can overlap on the same server without consuming extra capacity. Intervals are half-open ranges and jobs that run past midnight are truncated to the current day.
  • Follow-up: some jobs are long-running and span multiple days without restarting. For those, you want a dedicated server that isn't shared with other jobs. How would you detect which jobs need a dedicated server and how does that change your total server count calculation?

“Looked like a classic meeting rooms problem until the same-job-ID overlap rule hit me.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview, product strategy question about a real Google product. Pretty much a single question format, no warm-up, just straight into it.
  • How would you increase the conversion rate for YouTube Premium?

“I went straight to the funnel and started listing friction points, which felt right in the moment but I think I skipped past defining what 'conversion' even meant here.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE interview with a digit-matching array problem. Pretty clean problem once you see the trick, but I spent too long second-guessing myself on the approach.
  • Given a list of two-digit integers (10 to 99), find the maximum number of elements you can select such that all selected numbers share at least one common digit.

“My first instinct was some kind of greedy with frequency counting, which was actually right but I took forever to convince myself.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview with a single product design question. Pretty open-ended, which I wasn't fully prepared for.
  • Design a voting app.

“Spent the first couple minutes just trying to figure out what kind of voting they meant.”

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Google·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Google SWE coding round with a stream-processing problem that looks deceptively simple until you actually think through the edge cases. The follow-up questions pushed toward real-time query support which is where things got interesting.
  • Given a stream of user pair events representing active communications, process them in order while ignoring duplicates (regardless of order) and self-pairs, then return all users sorted by their distinct communication count descending, breaking ties by user id lexicographically ascending.
  • How would you modify your solution to return only the top K users by communication count instead of the full sorted list?
  • How would you support live queries asking for the current most-active user at any point during the stream, without re-sorting from scratch each time a new event arrives?

“My first instinct was to just throw everything into a set of sorted tuples and a counter dict, which is basically right, but I fumbled the tie-breaking for a bit.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
PM case question for Google, framed around a partnership pricing scenario between HBO Max and Roku. Pretty open-ended and I wasn't sure if they wanted a number or a framework, so I kind of fumbled the landing.
  • You're a PM at a video streaming service. A hardware partner wants to add a dedicated button for your app on their new remote control. How much should your company pay for this placement?

“I went straight to user acquisition costs and tried to back into a number from LTV minus CAC, which felt logical but I think I skipped over the strategic angle entirely.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview for Tiltbrush, their VR painting app. Single question focused on prioritization, which sounds straightforward until you realize the product lives in a pretty niche corner of the market and you have to actually know something about VR constraints to give a real answer.
  • You're the PM for Tiltbrush, Google's VR painting app. Walk me through how you'd prioritize features and improvements for the product.

“I fumbled the setup a bit because I started talking about user segments before I'd even established what success looks like for a VR creative tool.”

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Google·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Interviewed for a frontend engineer role at Google, just the one behavioral question from what I can tell.
  • What are your weaknesses?

“Classic question, still managed to fumble it a bit.”

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