Katkat

Company

Meta interview questions

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

Questions666

54 easy472 medium140 hard

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Meta interview questions by the numbers

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Katkat has 666 Meta interview questions. The largest topics are Coding & Algorithms (32%), Analytics & Experimentation (17%) and Behavioral & Leadership (11%). By difficulty: 8% easy, 71% medium and 21% hard. The most common round is Onsite (54%). Frequent concepts include System Design, Causal Inference, Algorithms and Scalability.

Difficulty

  • Easy8% · 54
  • Medium71% · 472
  • Hard21% · 140

Interview rounds

  • Onsite54% · 358
  • Technical Screen40% · 268
  • Online Assessment3% · 23
  • HR Screen2% · 10
  • Other1% · 7

Roles

  • Software Engineer43% · 285
  • Data Scientist39% · 262
  • Machine Learning Engineer11% · 70
  • Data Engineer3% · 21
  • Product Manager2% · 13

Frequent concepts

  • System Design4% · 28
  • Causal Inference3% · 20
  • Algorithms3% · 19
  • Scalability3% · 19
  • Distributed Systems2% · 14
  • Metrics2% · 14

Showing 661–666 of 666 results

  • This question evaluates SQL-based data manipulation and product-analytics competencies, including temporal sessionization, graph connectivity inference for detecting overlapping 1:1 call loops, deduplication trade-offs (UNION vs UNION ALL), and computation of derived metrics to estimate latent feature demand within the Data Manipulation (SQL/Python) domain. It is commonly asked because it measures practical application of event-time windowing, connected-component reasoning and edge-case handling (e.g., excluding failed connections) for producing daily summary metrics, emphasizing hands-on SQL proficiency over purely conceptual understanding.

    MetaData ScientistData Manipulation (SQL/Python)Technical Screen
  • This question evaluates proficiency with SQL window functions and equivalent pandas operations for KPI anomaly detection, covering baseline computation using same-weekday medians over eight weeks, per-country and per-post_type Likes-per-DAU metrics with deduplication of users for DAU, outage filtering, attribution of declines between new and existing users, and time-series comparisons like friend-request acceptance rates while explicitly handling duplicates, sparse or missing DAU rows, and timezone issues. It is commonly asked in Data Manipulation (SQL/Python) interviews to assess practical data engineering and analytical skills, primarily testing practical application with an underlying need for conceptual understanding of baselining, attribution, and data-quality edge cases.

    MetaData ScientistData Manipulation (SQL/Python)Onsite
  • This question evaluates practical SQL data-manipulation skills such as joins, aggregation, window functions, time-based filtering, deduplication, and computation of sales KPIs for rep-level analytics.

    MetaData ScientistData Manipulation (SQL/Python)Technical Screen
  • This question evaluates SQL and data-manipulation proficiency, including temporal joins, versioning, time-bounded snapshotting, windowed aggregations, and validation checks for data quality and idempotency.

    MetaData ScientistData Manipulation (SQL/Python)Onsite
  • This problem tests your ability to manage relational data, handle temporal overlaps for booking availability, and derive insights from social graph-like connections using SQL or data manipulation scripts.

    MetaData EngineerCoding & AlgorithmsTechnical Screen
  • Compare independent versus blocked ad insertion in a 100-post feed. Includes expected ads, tail risk, consecutive ad probabilities, longest streaks, product tradeoffs, and A/B test design.

    MetaData ScientistAnalytics & ExperimentationOnsite

Meta interview experiences

All 83 →
  • Full Onsite Loop Plus My AI Coding Interview PlaybookMeta · Software Engineer · Onsite · Sep 2026

    Most of the questions were the classic, well-worn ones you'd already find on the forum. Phone Leetcode easy + mid Onsite 2 AI coding rounds + 2 AI system design rounds + 1 BQ AI coding 01: Friend system: Implement a friend recommendation algorithm Given data: a list of users, a list of friendships (user-user pairs) Design a strategy to recommend new friends to a user (e.g., search for friends of…

  • Leadership and Fullstack Phone Screen, Rejected Over 'Not Enough Impact'Meta · Data Engineer · Senior+ · Technical Screen · Sep 2026
    Rejected

    From the recruiter to the interviewers, the whole thing gave off an absurd vibe. I was applying for a senior position, and the job description didn't even list a level at the time. After I applied, the recruiter had me submit my availability directly — no call at all. Once it was scheduled, I was told it would be one Leadership round and one Fullstack round. I thought that was a little strange at…

  • Offer After 1.5 Years Out of Work and 600+ Hours of PrepMeta · Software Engineer · Onsite · Sep 2026
    Offer

    I had been out of work for a year and a half. Once I got properly serious about the search, I fired off about 100 applications and basically got silence. A few startups got in touch, but nothing picked up speed. Then someone referred me at Meta and a recruiter asked to set up a call. One choice early on, I believe, defined everything that followed. I turned the startup conversations down and comm…

  • Explaining an AI System and Solving a Maze with AIMeta · Software Engineer · Technical Screen · Aug 2026

    This will most likely become a rejection story. At the beginning, I was asked to introduce an AI system I had designed and explain the problem it solved. I stumbled through the explanation, and the interviewer did not seem very satisfied. I probably did not make the project sound impressive enough. Next came AI coding. This really felt like a company going all in on AI, because everything involve…

  • Phone Screen Plus a Four-Round Virtual OnsiteMeta · Software Engineer · Onsite · Aug 2026

    Meta phone screen + virtual onsite writeup, with the questions and my thought process included. Since I signed an NDA, I'm coding the problem names as homophones — sorry about that. Phone Screen 45 minutes, two questions. The first five minutes were self-intro, and pretty much the rest of the time was spent coding. Question 1, coded 1091: a 2D grid, get from the top-left corner to the bottom-righ…

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