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Google interview notes, page 122 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
Google SWE coding round, one problem the whole time. It was a twist on the classic median-of-two-sorted-arrays problem but with run-length encoding thrown in, so you couldn't just decompress and brute force your way through it.
  • Given two sorted arrays in run-length encoded form (each as a list of value-frequency pairs), find the median of the fully merged array without decompressing it. Target O(log(m+n)) time.

“I knew the base LC 4 problem well enough, but the RLE wrapping genuinely slowed me down.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Interviewed for a PM role at Google and got a product sense question about a bad experience with a low-tech product. Pretty open-ended, which I wasn't fully prepared for.
  • Tell me about a time you had a frustrating experience with a low-tech product.

“I blanked for a second because I kept thinking of apps and software.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
PM interview at Google with a product metrics question framed around Spotify. One question, fairly open-ended, and I left feeling like I probably undersold the experimentation angle.
  • You're a PM at Spotify. What metrics would you use to decide whether to ship a new song recommendation algorithm?

“I jumped straight to engagement metrics like streams and skip rate, which felt right but also pretty obvious.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google coding interview, one question about sliding windows. Short and to the point, not much else to say about it.
  • Given an array of integers and a number k, find the subarray of length k with the minimum sum.

“Classic sliding window.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Went through a product sense interview at Google, just one question but it required a lot of unpacking. The question was framed around WhatsApp which felt a bit odd for a Google interview, but whatever.
  • What metrics would you measure to evaluate the success of a new feature on WhatsApp?

“I fumbled the opening a bit because I jumped straight into engagement metrics without clarifying what kind of feature we're talking about.”

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Google·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
Google PM interview, one question about growing revenue for an existing product. Pretty open-ended, no hints on scope or constraints.
  • How would you triple the revenue of Google Photos?

“I went straight to ads and storage upsells which felt obvious in retrospect, maybe too obvious.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Fermi estimation question at Google, classic stuff. One question, no real context given about the role or outcome.
  • How many quarters would you need to stack to match the height of the Empire State Building?

“These estimation questions always feel deceptively easy until you're actually doing the math out loud.”

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Google·Data Scientist·Technical Phone Screen

Jun 2026
Google Data Scientist interview that centered on a single algorithmic problem about detecting streak segments in event sequences. The problem had multiple follow-up layers and felt more like a coding round than anything DS-specific.
  • Given a time-ordered sequence of typed events, define what makes a contiguous subsequence a valid 'streak segment' and explain when a segment ends.
  • Design an algorithm to count the number of 'super streak' segments, where a super streak has at least N events and a duration of at least X.
  • What are the edge cases and complexity of your solution?
  • How would you adapt the solution if N, T, or X can change dynamically over time or per event?
  • How would you handle this problem if events arrive as an unbounded stream rather than a stored list?
  • How would you efficiently answer many different parameter queries (varying N, T, and X) on the same event sequence?

“This part felt straightforward but I second-guessed the inclusive gap condition.”

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Google·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Google system design round focused entirely on SLI/SLO/SLA concepts and building a production-grade alerting system. Pretty dense for a single session and the error budget math caught me off guard more than I expected.
  • Explain the differences between SLI, SLO, and SLA using a real web API as your example, covering both availability and latency.
  • Given a quarterly SLO target, define a reasonable error budget and walk through how you'd allocate and track its consumption over time.
  • Design a monitoring and alerting system that reduces alert fatigue. Cover which signals to alert on, how thresholds relate to SLOs, alert aggregation and deduplication, multi-window burn rate policies, and escalation and runbook practices.

“I knew the definitions cold but stumbled when they pushed me to give concrete numbers.”

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Google·Software Engineer·Technical Phone Screen

Jun 2026
Google SWE coding round, one question on subarray sums. Pretty standard algorithmic problem but the O(n) solution requires you to actually know the prefix-sum trick, which I'd practiced but still fumbled explaining cleanly under pressure.
  • Given an integer array and an integer k, find the total number of contiguous subarrays whose elements sum to k. Walk through an efficient solution.

“I knew this one.”

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