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Google interview notes, page 70 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 - Product Sense / Strategy

May 2026
Google interview with a single revenue estimation question for what seemed like a product or business analyst type role. Not much context given but the question itself is a classic.
  • Estimate the annual revenue generated by Google Ads.

“This one sounds straightforward until you actually try to structure it.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google product design interview, one question, no fluff. Just 'design a smart shoe' and then silence while you figure out what that even means.
  • Design a smart shoe. Walk through your product thinking.

“I spent the first minute just staring at the problem trying to figure out if this was a trick.”

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Google·Software Engineer·Onsite - Product Sense / Strategy

May 2026
Interviewed for a bizops role at Google, got a strategy question about restaurant revenue that felt more like a consulting case than anything ops-related.
  • What advice would you give to a new restaurant trying to grow its revenue?

“I went straight to the obvious stuff, foot traffic, upselling, delivery platforms, and I could tell midway through it wasn't landing as a structured answer.”

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Google·Product Manager·Onsite - Behavioral / Leadership

May 2026
Interviewed for a PM role at Google and got hit with the classic failure question. Not much else to say, just one question shared here.
  • What was your biggest failure as a product manager?

“I had an answer prepared but it still felt weird saying it out loud.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Google PM interview with a single big product deep-dive question that covers basically everything: product sense, metrics, feature design, prioritization, and stakeholder management all rolled into one. It's the kind of prompt that sounds manageable until you realize how much ground you're supposed to cover.
  • Pick a product you use regularly. Walk through who it's for, what its core goal is, and what metric you'd use to measure success. Then propose a new feature, explain the user problem behind it, describe how you'd build and prioritize it, define success metrics, outline any experiments you'd run, and explain how you'd get cross-functional buy-in.

“This is basically a full PM loop compressed into one question.”

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Google·Software Engineer·Technical Phone Screen

May 2026
Google SWE coding round, one main string problem with a follow-up. Pretty focused session, nothing too wild, but the edge case conversation took up more time than I expected.
  • Given a string and a target string, count how many substrings of the original string have the target as a prefix.
  • Follow-up: find the minimum length of a substring that contains the target string.

“My first instinct was to just slide a window and check prefix matches, which works fine.”

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Google·Software Engineer·Onsite - Multi Round

May 2026
Did my onsite loop for a Business Systems Analyst role at Google, SCM-focused. Four rounds total, two done and two still pending. First round felt genuinely solid, second one was rougher and the interviewer had his camera off the whole time which threw me off a bit. Now I'm sitting here doing the math on whether a mixed scorecard can still get through HC.
  • Conceptual definitions related to supply chain management domain knowledge.
  • SQL query problem as part of a domain and solution design round.
  • Solution design problem within a supply chain management context.

“Blew two of these.”

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Google·Software Engineer·Onsite - Coding / Algorithms

May 2026
Google SWE interview that went deep on dynamic programming, specifically knapsack variants. They wanted both implementations and a dry-run on actual inputs, which I was not fully expecting.
  • Implement the 0/1 knapsack problem: given item weights, values, and a capacity W, return the maximum value achievable and reconstruct the actual set of items chosen. Provide both the full O(nW) time and space DP table solution and a space-optimized O(W) space version.
  • Extend the 0/1 knapsack to a bounded variant where each item has a maximum count it can be used. Implement an efficient O(nW) solution using binary decomposition of item counts, and walk through the complexity and memory trade-offs.
  • Dry-run both the 0/1 and bounded knapsack solutions on the input: weights=[2,3,4], values=[4,5,10], capacity=7 for the 0/1 case, then add counts=[3,1,2] for the bounded case. Trace through the DP table step by step.

“The two-table vs rolling-array distinction is where I fumbled a bit.”

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Google·Software Engineer·Onsite - Coding / Algorithms

May 2026
Google SWE coding round where the main problem was straightforward enough, but the real test came in the follow-up about scaling to massive inputs. The interviewer wanted a structured walk through constraints and design choices, not just a buzzword dump about distributed systems.
  • After solving the in-memory version of the problem, the interviewer asked: what would you do if the input were extremely large?
  • How would your approach change if the problem specifically required sorting the full dataset?
  • What if there's severe key skew in the data?
  • What approximate data structures could be useful when exact answers aren't required?
  • How would you verify correctness when processing data in chunks rather than all at once?

“My first instinct was to say 'just use MapReduce or something distributed' and I could tell that wasn't landing.”

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Google·Software Engineer·Onsite - Multi Round

May 2026
Went through the full Google SWE onsite loop and came out with a mixed bag. Three rounds went well, including a graph problem where I got through the follow-up, but one string problem round went sideways and I ran out of time before writing any code. Now waiting to see if the hiring committee weighs the stronger rounds enough to offset that one.
  • Graph traversal or pathfinding problem, with a follow-up extension after the main solution.
  • String manipulation or parsing problem under timed conditions.

“This was the round I actually felt good about.”

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