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Google interview notes, page 138 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

Jun 2026
Interviewed for a security analyst role at Google, got asked a foundational question about the CIA triad. Pretty standard stuff but still worth thinking through how you'd frame it under pressure.
  • Can you explain the CIA triad and what each component means in the context of information security?

“Knew this cold, confidentiality, integrity, availability, but I rambled a bit trying to give examples for each one and I could tell the interviewer was waiting for me to just stop.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google interview with a classic creative/design thinking prompt. Not much context to go on but the question itself is pretty memorable.
  • You're given a pile of plastic straws. What can you build or create with them?

“I froze for a second because I kept waiting for a constraint that never came.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE coding round, pretty much one meaty scheduling problem the whole time. The follow-up about optimizing for future meetings added a wrinkle I wasn't fully ready for.
  • Given a list of meeting time intervals (start, end), find the minimum number of meeting rooms needed to schedule all of them without conflict. As a follow-up: how would you optimize for meetings scheduled far in the future?

“Got the core part fine, sorted by start time and used a min-heap to track end times.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE interview with a frequency-based array problem. Pretty standard algorithmic round but the follow-up on optimizing beyond the heap solution is where things get interesting.
  • Given an integer array and an integer k, return the k most frequent elements in the array.

“I went straight for the hashmap plus min-heap approach which works fine, O(n log k).”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Coding interview at Google for a Software Engineer role. The question itself wasn't brutal but the execution was shaky, lots of fumbling mid-explanation before things came together. Still has a behavioral round left and is genuinely unsure if this was enough to move forward.
  • Given an algorithm problem, optimize from a brute force solution to an optimal one, then analyze time and space complexity, and finally reduce space usage to O(1).

“Panicked mid-explanation trying to derive the optimal approach on the fly and just started fumbling the math out loud.”

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Google·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Interviewed at Google for a machine learning or MLOps-adjacent role. One question about keeping deployed models current. Short post, not a lot to go on.
  • How do you ensure a deployed model stays up to date over time?

“Talked about monitoring data drift and setting up retraining pipelines triggered by performance degradation.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview with a single case question about Waymo insurance pricing. Pretty open-ended, no obvious right answer, which was either freeing or terrifying depending on how you look at it.
  • Google opens Waymo's driverless fleet to the general public. How would you set insurance pricing for the program?

“I went straight to risk segmentation and kind of forgot to question the business model first, which I think hurt me.”

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Google·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Google SWE coding round with one simulation problem that looks manageable until you realize the assignment policy has to be exact or your example output is just wrong.
  • Given a list of car rental bookings (each a half-open interval [start, end)), assign bookings to the minimum number of cars using a specific deterministic policy: sort bookings by start, then end, then original index; always assign to the lowest-numbered free car; spin up a new car only when none are free. Return the car number that handled the most bookings, with ties broken by smallest car number.

“The interval scheduling part felt familiar but the strict assignment policy is where I got tripped up.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Interviewed at Google and got asked about sorting algorithm complexities. Pretty standard stuff but worth knowing cold.
  • What are the time complexities of Quick Sort and Merge Sort?

“Knew this one but still fumbled the average vs worst case distinction for Quick Sort.”

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Google·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Behavioral round at Google for an EM role. Just the one question from what I can tell, but it was a meaty one about managing working style differences with a direct report.
  • Describe a situation where a mismatch in working styles between you and a direct report affected the quality or pace of work.

“I had a story ready but I kept second-guessing whether it was senior enough.”

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