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Google interview notes, page 44 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·Technical Phone Screen

Apr 2026
Google SWE coding round, one problem the whole session. Seemed straightforward at first glance but the constraints made it interesting.
  • Given an integer array and an integer k, find the maximum sum of a contiguous subarray where the absolute difference between the first and last elements equals exactly k. Return 0 if no such subarray exists.

“My first instinct was brute force, check every pair of indices where the endpoints differ by k and track the max sum.”

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Google·Software Engineer·Onsite - Behavioral / Leadership

Apr 2026
Google behavioral round focused on how you handle chaos. One question, but it had a follow-up with teeth.
  • Tell me about a time you worked on a team with no clear ownership or defined processes. What did you actually do to bring structure, and how did you know it was working?

“The first part I had a decent story for.”

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Google·Software Engineer·Technical Phone Screen

Apr 2026
Interviewed for a business analyst role at Google and got hit with a retention-focused analytics question that was more open-ended than I expected.
  • How would you use cohort analysis to identify retention issues in a product?

“I started talking about grouping users by signup date and tracking how many came back week over week, which felt right, but I fumbled when they pushed on what I'd actually do once I spotted a drop-off.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Google PM interview, one product sense question about redesigning Maps for an older audience. Short and focused, not a lot of context to go on.
  • How would you improve Google Maps for grandparents or elderly users?

“I jumped straight into accessibility stuff like bigger text and voice prompts, which felt a bit obvious in retrospect.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Google PM interview with two questions focused on a payments feature inside a chat app. Pretty standard product sense territory but the metrics follow-up is where things get interesting.
  • How would you go about launching a peer-to-peer payment feature within a chat application?
  • How would you measure success for this feature?

“I went straight to user segmentation and almost forgot to talk about trust and security, which is kind of the whole product for payments.”

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Google·Software Engineer·Onsite - System Design / Architecture

Apr 2026
Google data engineer interview focused on system design, specifically building an ETL pipeline for a machine learning platform on AWS. Pretty technical and open-ended, which I wasn't fully prepared for.
  • Design an ETL pipeline for a machine learning platform running on AWS.

“This is a big open-ended question and I spent the first few minutes just trying to scope it properly.”

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Google·Software Engineer·Onsite - Multi Round

Apr 2026
Went through the full Google Software Engineer loop, phone screen plus four onsite rounds, and got rejected at the recruiter level before hitting the hiring committee. The recruiter said it was close and is now reviewing me for a lower level instead. One interviewer was genuinely bad and I'm still not over it.
  • HashMap-based coding problem with multiple follow-up questions and discussion.
  • Behavioral questions around handling customer needs and navigating ambiguous situations.
  • Graph traversal or graph-based algorithmic problem.
  • A hard algorithmic problem likely requiring divide and conquer or a segment tree approach.

“Phone screen went pretty well.”

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Google·Machine Learning Engineer·Technical Phone Screen

Apr 2026
Google MLE interview with a chunking algorithm problem, a follow-up variant of a previous round's question. The twist this time was a header constraint that changes how you think about the minimum chunk calculation.
  • You have a data header and a data payload. The header cannot be split across chunks. Given a max chunk size, find the minimum number of chunks needed to fit everything. When can the header share a chunk with the beginning of the data, and how does that affect your calculation?

“This is basically a part 2 of the classic chunk-splitting problem, but the header constraint is where it gets interesting.”

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Google·Machine Learning Engineer·Technical Phone Screen

Apr 2026
Google ML engineer interview with a dynamic programming problem on palindromic subsequences. Pretty standard algorithmic round, nothing flashy.
  • Given a string, find the length of its longest palindromic subsequence using dynamic programming.

“I knew the general DP approach but fumbled explaining the recurrence relation out loud.”

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Google·Software Engineer·Online Assessment (OA)

Apr 2026
Google SWE online assessment, one coding problem that's less about algorithms and more about reading a config file correctly and fixing broken code. The built-in AI tool was allowed which is a weird flex but okay. Felt more like a debugging/systems-thinking exercise than a typical LeetCode grind.
  • Given a config file defining features and their dependencies, fix buggy code so it correctly enables features based on user constraints (country, OS version), resolves transitive dependencies, and detects dependency cycles.

“The problem sounds manageable until you realize the bugs are subtle and the config parsing rules matter a lot.”

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