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Google interview notes, page 159 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·Business Analyst·Technical Phone Screen

Jun 2026
Google case interview, just one question about estimating motel counts in the US. Pretty classic market sizing, but I fumbled the structure more than I expected.
  • Estimate the number of motels in the US.

“I went with a population-based breakdown, splitting the US into urban, suburban, and rural buckets and working from there.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview with a classic product design question. Pretty open-ended, which sounds nice until you're actually sitting there trying to figure out where to start.
  • How would you design a bike-sharing system for your city?

“I started with user segments, which felt right, but I spent way too long on that part and rushed through the actual product decisions.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Graph question at Google, felt pretty standard until I started second-guessing my BFS approach mid-interview. The edge cases are where it gets messy and I didn't handle all of them as cleanly as I should have.
  • Given a directed graph and a target node, find the shortest cycle that passes through the target node, or determine that no such cycle exists.

“My first instinct was DFS and I had to walk it back, which cost me time.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview, product design question focused on supermarkets. One question, open-ended, and they really did expect you to pick a lane and go deep rather than give a surface-level tour of the whole problem.
  • Design a modern supermarket. Choose one specific area to focus on (like store layout, checkout flow, product discovery, or a loyalty program) and go deep: what clarifying questions would you ask, who are the target users, what does the MVP look like, and how would you measure success?

“I picked checkout flow because I thought it was the most concrete and I could riff on friction points I've personally experienced.”

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Google·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Google SWE coding round with a scheduling/greedy problem. Pretty clean problem statement but the follow-up about returning the actual car assignments added some complexity I didn't fully anticipate.
  • Given a list of rental records with pickup and return times, find the minimum number of cars needed to fulfill all rentals simultaneously. Return both the count and the assignment of rentals to each car.

“The core idea clicked pretty fast for me, sort by start time and use a min-heap to track when each car becomes free.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Applied to Google on a whim through their careers site and actually made it through two rounds with positive feedback, only to get stopped by a visa restriction issue that had nothing to do with performance.
  • Solve a problem using a priority queue as the core data structure.

“Felt pretty good about this one.”

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Google·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Google SWE coding round with a Mahjong hand validation problem. Classic backtracking/recursion territory, felt pretty clean on the surface but the edge cases sneak up on you.
  • Given 14 integer tiles representing a Mahjong hand, determine whether they can be partitioned into 4 melds (each a triplet of identical tiles or a sequence of three consecutive tiles) and 1 pair of identical tiles.

“My first instinct was to sort and greedily consume sequences, which is wrong and I knew it was wrong while doing it.”

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Google·Machine Learning Engineer·Technical Phone Screen

Jun 2026
Google ML Engineer interview with a coding round that pushed the classic packing problem into 2D territory. The geometric twist was unexpected and the discussion about scaling to higher dimensions felt like it could've gone on forever.
  • You have a stream of items, each with a 2D size vector. Identify all triple-packs where the maximum pairwise Euclidean distance among the three items falls below a given threshold. How do you do this efficiently?

“I knew the 1D version well enough, so my first instinct was to just sort by x and use binary search to filter candidates within the threshold range on that axis.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google coding interview for a software engineer role. One question, pretty algorithmic, the kind where you think you have it figured out and then realize there's a subtlety you almost missed.
  • Given a list of strings, group together any strings that share the same character-shift pattern. Two strings match if the differences between consecutive characters (mod 26) are identical across all positions.

“I got the basic idea pretty fast.”

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Google·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Google SWE coding round focused on matrix rotation, starting from the classic square in-place version and pushing hard into the rectangular case. The follow-ups were where things got uncomfortable.
  • Rotate an m×n 2D matrix 90 degrees clockwise. For a square matrix, do it in-place with O(1) extra space.
  • Follow-up: can you rotate a non-square (m×n where m ≠ n) matrix in-place? What are the trade-offs?
  • Further follow-up: rotate a subwindow inside a larger matrix 90 degrees clockwise while leaving the rest of the matrix unchanged.
  • What if you need to support rotations by arbitrary multiples of 90 degrees, or reflections across an axis?

“Knew this one cold.”

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