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Google interview notes, page 168 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 - Behavioral / Leadership

Jun 2026
Behavioral round at Google for a software engineering role. The whole thing felt less like a structured interview and more like a conversation that kept spiraling deeper into my resume. Come ready to defend every project you've ever listed.
  • Walk me through one of your most impactful projects. What was the goal, what did you personally own, and what trade-offs did you make along the way?
  • How did you drive alignment across teams or stakeholders when you didn't have direct authority over them?
  • Tell me about a time you raised the quality bar on your team. What did you change and how did you get others on board?
  • Describe a situation where you mentored someone or helped a teammate grow. What was your approach and what was the outcome?

“This is the anchor question and they will not let you stay high-level.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE coding round, pretty standard algorithmic problem but the trick is knowing the right data structure pattern. One question, clean setup, no behavioral stuff from what I remember.
  • You're given an array of zeros and a list of range update operations, each adding a value to every element between two indices inclusive. Apply all updates and return the final array as efficiently as possible.

“I knew there was a smarter way than looping through every range but my brain went to brute force first, which would've been O(n*k) for k updates.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Got a coding problem at Google for a SWE role that was basically a custom tokenizer using greedy longest-match against a dictionary. Felt like something you'd see in an NLP pipeline, which was a fun twist compared to the usual array/graph stuff.
  • Given a text string and a dictionary mapping tokens to integer IDs, process the string left to right: at each position, find the longest dictionary token that matches the current prefix, replace it with its ID in the output, and advance past it. If nothing matches, copy the character as-is and move one step forward. Return the final output string.

“The greedy part clicked pretty fast but I initially forgot to handle the 'no match' case properly and was just skipping characters instead of appending them.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google product design interview, one question about building an online marketplace for fruits and vegetables. Not a lot of context given upfront so I had to do a lot of the scoping myself.
  • Design an online marketplace for fruits and vegetables.

“I spent too long on the user personas and the interviewer had to nudge me toward the actual product decisions.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE interview with a string manipulation problem that seemed straightforward but had a decent follow-up about implementation tradeoffs. Nothing too wild but the follow-up is where it got interesting.
  • Given two strings, determine whether one can be constructed using only the characters available in the other, respecting character frequencies.
  • Follow-up: if the bag string is extremely large, how would you compare using a fixed-size integer array versus a HashMap for storing character frequencies, and when would you choose one over the other?

“Got to the frequency count approach pretty fast, just compare counts per character and you're done.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Got a PM case question from Google about YouTube and inappropriate content surfacing in family settings. Pretty focused single-question session, product sense style.
  • You're a PM at YouTube. Users are reporting that inappropriate videos sometimes play in family settings because the account is tied to an adult profile. How do you tackle this?

“I went straight to solutions and the interviewer had to pull me back to ask who exactly was affected and how often this happens.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Sat through a Google PM screen with one of those pricing/strategy curveballs that sounds straightforward but pulls you in five directions at once. Left the room not totally sure I nailed it.
  • If the manufacturing cost of Google Glass dropped to $10, what would you do?

“My first instinct was to just say 'lower the price and push volume' and I almost went with that.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview with a single product design question focused on accessibility. Pretty open-ended and I wasn't sure how deep to go on the technical side versus the user empathy side.
  • How would you design a smartphone for blind users?

“I jumped straight into features and kind of skipped the whole 'who exactly is this for' part, which I regretted mid-answer.”

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Google·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Google ML engineer interview with a coding question that looked trivial but had a specific efficiency angle worth thinking through carefully.
  • Given a list of natural numbers, sort both the numbers and their squares as efficiently as possible.

“My first instinct was to just square everything and sort the whole thing, which is fine but misses the point.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Interviewed for a PM role at Google and got hit with a classic platform strategy question about whether Google should keep running both Chrome OS and Android. Pretty straightforward product strategy territory but there's more nuance than it looks.
  • Should Google continue maintaining both Chrome OS and Android as separate operating systems?

“I went straight to user segmentation, which felt right.”

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