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Google interview notes, page 132 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 at Google for what seemed like a data center or infrastructure ops role. One scenario-based question about handling a fire in a data center. Short post, not much context to go on.
  • If a fire breaks out in a data center, what steps would you take?

“Tried to walk through it systematically: alert staff, trigger suppression systems, isolate affected zones, escalate to on-call leads, document everything.”

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Google·Data Scientist·Technical Phone Screen

Jun 2026
Brutal Google DS onsite question covering basically every dimension of A/B testing at once. The depth expected here is no joke, this is the kind of question where you can talk for 45 minutes and still feel like you left things on the table.
  • You're launching a personalized ranking feature on a product listing page. Define your primary success metric including the exact formula with numerator, denominator, and any data filters you'd apply.
  • Define at least three guardrail metrics with specific thresholds and explain what failure mode each one is protecting against.
  • Design the experiment: what's your unit of randomization and why, how do you handle exposure rules, pre-exposure filtering, stratification, and repeat visitors across devices?
  • Compute the required sample size to detect a 1.5% relative lift in the primary metric at 90% power with a two-sided alpha of 0.05, given a baseline mean of 3.2 and an SD of 2.1 per user-day. Show the formula.
  • What stopping rule would you use, how would you apply CUPED or re-randomization to reduce variance, and what SRM test would you run daily?
  • How would you visualize experiment results and diagnose issues, including quantile treatment effects, funnel breakouts, and time-since-exposure plots? How do you interpret heterogeneous treatment effects without p-hacking?

“I went with something like revenue per session filtered to sessions with at least one ranking impression, and the interviewer pushed back immediately asking why not per user or per page load.”

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Google·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Went through a Google SWE coding round with three problems. Two felt pretty standard but the unlock pattern one was genuinely tricky and I'm not sure I handled it well under pressure.
  • Given an integer N, return the N-th license plate in lexicographic order, where each plate has exactly 6 characters: the first 3 are uppercase letters (A-Z) and the last 3 are digits (0-9).
  • Count all valid Android-style 3x3 grid unlock patterns that use between 4 and 9 dots, where a move is only valid if any dot lying on the straight line between two points has already been visited.
  • Given two lists of non-overlapping, sorted closed intervals, return all intervals representing the intersection of the two lists.

“Basically a base conversion problem once you see it.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview, single estimation question about high school students in the US. Pretty short session, felt more like a warmup than a full round.
  • Estimate the number of high school students in the US.

“I started with total US population and tried to carve out the right age bracket, roughly 14 to 18, which is about 5 years out of an 80-year lifespan.”

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Google·Software Engineer·Onsite - Multi Round

Jun 2026
Went through the full Google loop for a software engineering role, split across two separate rounds about five months apart. The first batch was virtual, the second onsite. Four technical rounds total plus a behavioral one, and my self-ratings ranged from solid to pretty good across the board, though I'm still not sure what the outcome will be.
  • Given a binary search tree, find the longest path where all nodes share the same value.
  • Standard behavioral and culture-fit questions covering how you work, handle disagreements, and operate on a team.
  • Given a set of tasks and CPUs, schedule the tasks optimally. Follow-up: find the minimum number of CPUs required to achieve the best possible completion time.
  • Given a set of points on a plane, find the maximum area rectangle that can be formed using those points as corners.

“Virtual round, first technical question.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE coding round, basically one DP problem with a bunch of follow-ups layered on top. The core question wasn't too bad but the follow-ups pushed into territory I hadn't fully prepared for.
  • You're robbing houses on a street where adjacent houses share a security system. Given an array of non-negative integers representing house values, find the maximum amount you can steal without triggering the alarm by hitting two adjacent houses on the same night. Solve it in O(n) time and O(1) space using dynamic programming.
  • What are the time and space complexities of your solution?
  • Can you optimize the space usage further, and walk through how you'd justify that optimization?
  • Extend the solution to also return the actual list of house indices chosen in an optimal robbery plan, not just the maximum value. One valid plan is sufficient.

“Got through the basic solution fine, the recurrence isn't hard once you see it.”

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Google·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
Google SWE coding round, one linked list problem that looks straightforward until you hit the follow-up about doing it in constant space.
  • Given two singly linked lists that may merge at some point, find the first node they share. The lists can be different lengths, and intersection means same reference, not same value. Follow-up: can you do it in O(m+n) time and O(1) space?

“My first instinct was a hash set, which works fine but fails the space constraint.”

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Google·Software Engineer·Onsite - Multi Round

Jun 2026
Four rounds at Google for a software engineering role in Bangalore. Three coding rounds and a behavioral, with strong feedback across the board except for the third coding round where I missed an edge case and the interviewer ended things early. Recruiter said mixed-to-negative on that round but still moved me to team matching, so now I'm just waiting and overthinking it.
  • Implement a solution using topological sort.
  • Solve a dynamic programming problem on trees.
  • Solve an interval-based problem.

“Came up twice across different rounds which was a little surprising.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE coding round with a scheduling problem that looks deceptively simple until you realize the cyclic clock wraps around midnight and suddenly your interval logic is broken.
  • Given a list of tasks each with a start time and duration in minutes on a 24-hour cyclic clock (tasks can wrap past midnight), find the minimum number of servers needed so every task runs on a dedicated server for its full duration without any overlap.

“The example they gave was tasks like (23, 60) which wraps past midnight and that's where I fumbled at first.”

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Google·Software Engineer·Onsite - Behavioral / Leadership

Jun 2026
Standard behavioral screen for a Software Engineer role at Google. Five questions, nothing surprising, pretty much the classic set you'd expect from any big tech company doing this kind of round.
  • Walk me through your background and resume.
  • Tell me about the most challenging project you've worked on.
  • Describe a time you had a conflict with a teammate or manager and how you handled it.
  • Tell me about a time you failed and what you took away from it.
  • Why Google, and why this specific role?

“The opener.”

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