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Google interview notes, page 157 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 - Coding / Algorithms

Jun 2026
Google SWE coding round with a grouping problem that looks deceptively simple until you start thinking about transitive relationships between numbers.
  • Given an array of two-digit numbers (up to 100 elements), find the maximum size of a group where every number in the group shares at least one digit with at least one other number in the group.

“My first instinct was to just check pairwise digit overlap and greedily build groups, which completely fell apart once I thought about transitivity.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE interview, system design flavor, went deep on an indexing/query optimization problem. The follow-up questions kept stacking and by the third layer I was mostly just trying to keep up.
  • You've already narrowed candidates using signature buckets, but you're still recomputing run-length groupings for every candidate on each query. How would you optimize this further using precomputed per-group count vectors?

“This is the part where I started to lose the thread a bit.”

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Google·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Behavioral round at Google for a software engineering role, basically one question about team conflict and then it was over.
  • Tell me about a time you had a conflict with a teammate.

“I had a story ready but I rambled way too much on the context and barely had time to explain what I actually did to fix things.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google software engineer interview with a technical deep-dive into past project work. The main focus was a behavioral-style question that quickly turned into a technical grilling on decisions and trade-offs.
  • Walk me through a recent project you found both challenging and interesting. What made it hard, what broke down, and how did you fix it?

“The question itself sounds easy until you realize they're not just collecting a story, they want to pick it apart.”

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Google·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Google SWE interview, coding round focused on a data structure design problem that looked deceptively simple at first. The follow-up on concurrency is where things got real.
  • Design a data structure that supports insert, delete, and get-random-element, all in O(1) average time.
  • How would you extend that data structure to be thread-safe under concurrent add, delete, and get-random operations? Walk through at least two designs and compare them.

“I knew this one.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
PM interview at Google with a cost estimation question for Google Photos. Pretty classic product sense meets back-of-envelope math combo, nothing too wild but it requires you to actually know what goes into running a product at that scale.
  • Estimate the annual cost of managing Google Photos. What factors would you consider in your calculation?

“I started with storage since that's the obvious one, but then kind of froze trying to figure out whether to account for compression, deduplication, tiered storage across hot and cold buckets.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview with a system design flavored product question about building an experimentation platform. Pretty open-ended, which I wasn't fully ready for.
  • How would you design a system for running experiments like A/B tests on an app or website?

“I started with user assignment and bucketing logic, which felt right, but I think I spent too long there and barely touched metrics infrastructure or statistical significance.”

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Google·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Google SWE coding round, pretty much a classic scheduling problem with a few curveballs thrown at the end. Nothing shocking but the follow-ups kept it from being a total autopilot session.
  • Given an array of meeting time intervals, find the minimum number of conference rooms needed to schedule all of them without conflicts.
  • How would you adapt the solution if meeting intervals arrive as a stream rather than all at once upfront?
  • Can you modify the approach to also return which meetings are assigned to which room, not just the count?
  • How would you extend the solution if meetings had weights or priorities that affected how concurrency should be counted?

“Knew the heap approach going in, sort by start time, track end times in a min-heap, pop anything that's already finished before pushing the new one.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE coding round, one algorithmic problem that looked straightforward until I started thinking about edge cases with negative values scattered through the array.
  • Given an array of integers, find all pairs of indices where the values are equal, compute the subarray sum between each such pair, and return the maximum among those sums.

“My first instinct was brute force, just track every pair of matching values and sum between them.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview, one product improvement question about Day One. Not much else to go on but it's the kind of open-ended thing that can spiral fast if you're not careful about scoping.
  • How would you improve Day One (the journaling app)?

“The first instinct is to just list features, which is probably the wrong move.”

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