Google interview notes, page 181 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 - Coding / Algorithms

Jun 2026

Google SWE coding round with a piano hand movement problem that sounds cute until you actually have to think about it carefully. The follow-up added a printing requirement that changed how you'd want to structure the solution.

You're given an integer array. Imagine placing one hand on a piano keyboard. The hand can cover a range of consecutive keys at any position. Count the minimum number of times you need to reposition the hand to play all the keys in the array. For example, [1,2,3,4,5] requires 0 moves, [5,9,1] requires 1 move. Follow-up: each time you move the hand, print the group of keys played by the previous hand position, and also print the final group at the end.

“The base case clicked pretty fast.”

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Google·Software Engineer·Onsite - Coding / Algorithms

Jun 2026

Google SWE coding round with a frequency-based sorting problem. Pretty standard algorithmic stuff but the edge cases around tie-breaking tripped me up a bit.

Given an array of integers, return all distinct elements sorted by decreasing frequency. If two elements share the same frequency, sort them by increasing value.

“My first instinct was a hash map for counts, then sort with a custom comparator.”

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Google·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026

Behavioral round at Google for a software engineer role, pretty much one big leadership question with a bunch of follow-ups branching off it. Not a bad experience but I underestimated how deep they'd go.

Walk me through your leadership experience. How do you actually lead people?
Would you describe your leadership style as more directive or collaborative, and why?
Tell me about a time you had to deal with an underperformer on your team.
How do you give feedback to someone on your team, especially critical feedback?

“They wanted a concrete story, not a philosophy lecture.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026

Phone screen for a Software Engineer role at Google. One coding question on Quick Select, covering different approaches and pivot selection before implementing a solution.

Implement Quick Select. Walk through different approaches, discuss how you'd choose a pivot, then code up one of the methods.

“We spent a good chunk of time just talking through the tradeoffs before any code.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026

Got a product metrics question for a Google PM role. Pretty standard stuff but it made me realize how easy it is to just list metrics without actually tying them to what the product is trying to do.

If you were the PM for Google Drive, what metrics would you prioritize?

“I went straight to engagement stuff like DAU and storage usage, which felt safe but probably came across as shallow.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026

Google software engineering interview focused entirely on Union-Find. One coding round, pretty algorithmic, nothing behavioral from what I remember.

Solve a Union-Find problem such as finding the number of connected components, merging accounts, friend circles, or detecting a redundant connection in a graph.

“I knew Union-Find going in but froze a bit when they asked me to pick which variant to solve.”

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Google·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026

Behavioral round at Google for a software engineering role. Just one question but they kept pushing for more, which I wasn't totally ready for.

What makes a team a great place to work? Can you go beyond your first answer and give more reasons?

“I gave a decent first answer about psychological safety and clear ownership, felt pretty good about it.”

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Google·Machine Learning Engineer·Onsite - Coding / Algorithms

Jun 2026

Google ML Engineer coding round, one question the whole time. The problem looked familiar but the twist tripped me up a bit before things clicked.

Given an m x n binary matrix, count the total number of square sub-matrices of any side length (at least 1x1) that are made up entirely of 1s.

“I recognized this as related to the classic 'largest square of 1s' DP problem, which helped.”

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Google·Software Engineer·Onsite - Product Sense / Strategy

Jun 2026

Google product strategy interview focused on the Android ecosystem and how to keep OEM partners aligned with Google's services rather than building their own. Pretty open-ended and I spent most of my prep time on the wrong things.

Android fragmentation is growing as smartphone manufacturers push their own services instead of Google's. How would you approach working with OEMs to increase native adoption of Google services?

“This one is broader than it sounds.”

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Google·Software Engineer·Onsite - System Design / Architecture

Jun 2026

Staff-level onsite at Google for SWE, two back-to-back system design rounds plus a behavioral round. The bar is noticeably higher than senior: interviewers are explicitly comparing you against that level and the differentiator is decision depth, not how fancy your architecture looks.

Design a distributed rate limiter as an internal service supporting 100k+ QPS, multiple tenants, and multiple regions.
Design a global real-time notification system handling push, email, and SMS for 100 million+ users, including fan-out, retry logic, and deduplication.
Design an anomaly detection system. The domain is intentionally unspecified: you need to clarify whether this is metric streams, user behavior, or infrastructure alerts before proceeding.
Design a Find My Device system (similar to Find My iPhone), with explicit attention to privacy, security, and efficiency constraints.
Design a global menu update system for a chain restaurant, covering multi-region sync, offline-tolerant edge devices, and time-of-day menu variants.
Design a dictionary range query store: store a set of words and support a range query returning all words in a given lexicographic interval. Discuss trie structures, sorted indexes, and sharding approaches.
Walk through how your system handles failure scenarios: what happens when a region disconnects, when storage fails, or when a tenant abuses the system? Make concrete fail-open vs fail-close decisions.
Describe the evolution path for your design: how does it scale from an MVP to 10x and then 100x load? Where would you re-architect and how would you roll out the new design?

“The failure mode I kept seeing in prep (and honestly did myself the first few mocks) is jumping straight to 'token bucket on Redis' without asking who the tenants are or what the latency SLO is.”

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