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Google interview notes, page 108 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·Data Scientist·Technical Phone Screen

May 2026
Interviewed for a Data Scientist role at Google and got a Python coding question about list deduplication. Pretty standard algorithmic problem but the in-place vs return-new-list framing tripped me up for a second.
  • Write a Python function that removes duplicate elements from a list while preserving the order in which items first appeared.

“My first instinct was to just use a set and call it a day, which obviously kills the order.”

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Google·Software Engineer·Technical Phone Screen

May 2026
Google SWE interview focused entirely on performance optimization, which sounds straightforward until you're actually in it and realize how many angles they expect you to cover. The question was a single meaty problem but it touched profiling, algorithms, data structures, and Python internals all at once.
  • You're given a Python program that produces correct output but runs much slower than expected. Walk through how you'd profile it, identify the bottlenecks, apply fixes, and report the before/after performance improvement.

“This one is deceptively wide.”

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Google·Software Engineer·Online Assessment (OA)

May 2026
Google OA for a SWE role. One coding problem, pretty straightforward on the surface but the second example tripped me up a bit.
  • Given a list of integer tuples, return a sorted list of all the integers across those tuples in ascending order.

“The first example made it look like a trivial flatten-and-sort.”

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Google·Software Engineer·Online Assessment (OA)

May 2026
Google SWE online assessment with a probability/dynamic programming problem that looks approachable until you actually think about it. The problem is well-defined but the edge cases are sneaky.
  • You start at position 0 on an infinite 1D integer grid. Each step you roll a K-sided die (values 1 through K, uniform) and move forward by that amount. Given a target interval [mn, mx], you win if you land anywhere inside it, and lose if you overshoot past mx without ever entering it. Compute the probability of winning.

“Took me a while to even convince myself the recursion was right.”

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Google·Software Engineer·Onsite - Coding / Algorithms

May 2026
Google SWE coding round with a sliding window problem that had a twist I wasn't fully prepared for. The core idea isn't hard but the exclusion mechanic tripped me up a bit on the implementation.
  • Given an integer array, a window size, and an integer k, slide a window across the array one step at a time. For each window, remove the k largest elements and return the average of what's left. Return all such averages as an array.

“I got the sliding part pretty quickly but fumbled on efficiently dropping the k largest.”

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Google·Software Engineer·Onsite - Behavioral / Leadership

May 2026
Behavioral round at Google for a software engineer role. Pretty much the whole thing was conflict-related questions, which I wasn't fully prepared for going in.
  • Tell me about a time you had to resolve a conflict with a teammate or colleague.

“They kept coming back to conflict scenarios from multiple angles.”

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Google·Software Engineer·Onsite - Coding / Algorithms

May 2026
Google SWE interview with a simulation/algorithm question that had a deceptively tricky tie-breaking system. Got through the logic but ran out of time before a clean dry-run, and the interviewer caught a couple bugs.
  • You're given a sorted array where each index represents a person and each value is a tuple of (timestamp, 'enter' or 'exit'). Return an array where each index is a person and each value is the time they actually enter or exit, after applying tie-breaking rules: if the previous moment had an enter, enters get priority; if it had an exit, exits get priority; if nothing happened, exits get priority; and for simultaneous actions, lower index goes first.

“The tie-breaking rules are where this gets messy.”

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Google·Software Engineer·Onsite - Behavioral / Leadership

May 2026
Behavioral round at Google, one of those quality-focused questions about catching a bug late in the release cycle. Pretty standard for a senior engineering role but the follow-up on how I managed the situation is where things got interesting.
  • Tell me about a time you caught a critical defect right before a major product launch. What steps did you take to handle it?

“I had a decent story ready for this but I fumbled the second part.”

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Google·Software Engineer·Technical Phone Screen

May 2026
Google SWE interview with a math-heavy coding question about license plate enumeration. The whole thing hinged on figuring out a closed-form solution, no brute force allowed.
  • License plates follow the format of three uppercase letters (A-Z) followed by three digits (0-9), giving plates like AAA000 through ZZZ999. If you sort all valid plates lexicographically, how do you find the Nth plate (1-indexed) in O(1) time without iterating through them?

“I stared at this for an embarrassingly long time before realizing it's basically a mixed-radix number decoding problem.”

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Google·Product Manager·Onsite - Product Sense / Strategy

May 2026
Product sense round at Google for a PM role, just one question but it had a lot of surface area to cover.
  • How would Google enter the food delivery market?

“I went straight to competitive landscape and probably spent too long there.”

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