Katkat

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Google interview questions

486 practice questions in the style of Google's interviews, covering Behavioral & Leadership, Coding & Algorithms, Machine Learning, Statistics & Math, Data Manipulation (SQL/Python), Analytics & Experimentation, Product / Decision Making, Software Engineering Fundamentals, ML System Design, System Design, Product Design & Strategy.

Questions486

35 easy348 medium103 hard

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Google interview questions by the numbers

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Katkat has 486 Google interview questions. The largest topics are Coding & Algorithms (40%), Behavioral & Leadership (19%) and System Design (8%). By difficulty: 7% easy, 72% medium and 21% hard. The most common round is Technical Screen (52%). Frequent concepts include Data Structures, Greedy, Algorithms and Optimization.

Topics

Difficulty

  • Easy7% · 35
  • Medium72% · 348
  • Hard21% · 103

Interview rounds

  • Technical Screen52% · 253
  • Onsite42% · 204
  • Online Assessment2% · 12
  • Other2% · 10
  • HR Screen1% · 7

Roles

  • Software Engineer65% · 317
  • Data Scientist20% · 96
  • Machine Learning Engineer7% · 35
  • Product Manager5% · 25
  • Data Analyst1% · 5

Frequent concepts

  • Data Structures5% · 24
  • Greedy5% · 22
  • Algorithms4% · 21
  • Optimization4% · 19
  • Arrays3% · 17
  • Graph3% · 14

Most mentioned in interview experiences

  1. 1.Choose Your Workplace Style3 reports
  2. 2.Select MOST/LEAST appropriate actions (SJT)3 reports
  3. 3.Choose best/worst actions in workplace ethics scenarios2 reports
  4. 4.Choose Non-Overlapping Weighted Jobs to Maximize Total Profit2 reports
  5. 5.Decide string transform with directional tokens and walls2 reports
  6. 6.Describe a conflict with a colleague2 reports
  7. 7.Describe a major challenge you faced2 reports
  8. 8.Design a Spam Review Workflow with Classifiers, AI Agents, and Human Labelers2 reports
  9. 9.Explain handling a tight project deadline2 reports
  10. 10.Grid Reachability From Start to Target With Impassable Water Cells2 reports

Counted from 74 candidate interview experiences on Katkat. How we collect and count

Showing 481–486 of 486 results

  • Which Area Would You Improve Now to Do Better Work at Google?Medium

    A behavioral question from a Google software engineer onsite that asks which area you would improve about yourself right now and how that improvement would help your future work at the company. It tests self-awareness, honesty about a real gap, a credible development plan and a clear link to the role.

    GoogleSoftware EngineerBehavioral & LeadershipOnsite
  • Why Google, Handling a Rejection, and What You Expect From a ManagerMedium

    A two-part behavioral interview: explain why you want to work at Google and what you would do if you did not pass, then describe what you expect from a manager and how you would act as one when handling delivery, conflicts between leadership and the team, and requests for extra effort.

    GoogleSoftware EngineerBehavioral & LeadershipOnsite
  • Why Would Users Care and Why Build It?Hard

    Build a product strategy answer for a Google AI productivity assistant across Search, Gmail, Docs, and Calendar. Covers user pain points, MVP, 15-year vision, VP pitch, Google advantages, metrics, and risks.

    GoogleProduct ManagerProduct Design & StrategyTechnical Screen
  • Write SQL and merge linked listsMedium

    Solve a SQL customer order aggregation task and merge two sorted linked lists. The solution uses CTEs, window functions, LEFT JOINs, COALESCE, latest-order tie handling, optional returned-order filtering, and an O(m+n) dummy-head linked-list merge.

    GoogleData EngineerCoding & AlgorithmsTechnical Screen
  • Write SQL/Python for messy event dataMedium

    This question evaluates SQL and pandas proficiency for event-level data manipulation, including time zone–aware local date conversion, session-based deduplication, cohort and conversion metric calculation, and basic experiment sanity checking via a sample-ratio-mismatch p-value.

    GoogleData ScientistData Manipulation (SQL/Python)Technical Screen
  • YouTube Data Throughput EstimationMedium

    Practice a YouTube daily data throughput Fermi estimate using daily users, watch time, average bitrate, overhead, unit conversions, sensitivity analysis, sanity checks, and a final exabytes-per-day range.

    GoogleProduct ManagerProduct / Decision MakingTechnical Screen

Google interview experiences

All 103 →
  • A Huge YAML Merge Problem and a Knapsack That Wants QuickselectGoogle · Software Engineer · Intern · Technical Screen · Oct 2026

    The first-round interviewer was really nice, but the problem was super long. Reading and understanding the problem plus the examples can take maybe 20 minutes. Roughly, it is merging two trees (YAML files), where every node has merge rules, and there are a lot of rules. The approach is DFS plus rule matching. The second-round interviewer gave me a knapsack problem, but for this one DP or DFS with…

  • Back-to-Back Phone Screens: Behavioral, Then an HTTP RouterGoogle · Software Engineer · Technical Screen · Oct 2026

    After I finished the psychological test, they scheduled my phone interviews right away. It was two rounds back to back, 45 minutes each, and I don't know if that's normal. The first round was a behavioral round with a really nice interviewer. All the questions were the usual ones: what do you do if you disagree with a coworker, what do you do if you disagree with another team, what do you do if a…

  • In-Person Onsite with a Design Round and a Train Schedule QuestionGoogle · Software Engineer · Onsite · Oct 2026

    The onsite was in-person (but virtual was an option) and only two rounds. I only had 4 interviews total with Google. Onsite was solutions design and Leetcode question. Solutions design question was design a review ingestion platform for an e-commerce site that takes reviews and summarizes them with an LLM for an internal dashboard. Focus on trust and safety, prompt injection, data sanitization, P…

  • 10-Minute Resume Grill, Then First Missing Positive in O(1) SpaceGoogle · Software Engineer · Intern · Technical Screen · Sep 2026

    The interview started right on time and went straight into an intense 10-minute resume grill. The interviewer homed in on my recent backend work, specifically asking detailed questions about the Kafka streaming architecture and Redis caching implementations from my previous internship in the Platform Cloud org. They also dug into the technical trade-offs I made when building Bastion, focusing hea…

  • An Unexpected Forecasting Question and a Fast Offer TimelineGoogle · Data Scientist · Onsite · Sep 2026
    Offer

    I signed Google's offer a couple of days ago, though I still have a few other issues to resolve. I'm sharing my interview experience and preparation package, and hoping I can start smoothly. First round Stats: Questions about p-values, simple linear regression, confidence intervals, and similar topics. Data: Compare two vendors' models. There are similar questions in other interview reports. Seco…

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