Meta Interview Questions

Meta Behavioral & Leadership Interview Questions

Practice 1,166 real Meta interview questions for 2026. Covers top categories — Coding & Algorithms, Analytics & Experimentation, Data Manipulation (SQL/Python), Behavioral & Leadership, and System Design — across Software Engineer, Data Scientist, Machine Learning Engineer, Data Engineer, and Product Manager roles. Real questions from actual interviews with detailed solutions. Expect a software-engineering-heavy loop: timed algorithmic coding (trees, arrays, graph/maze problems, delimiter/CSV parsing), system-design prompts like leaderboards, flight search and online-judge architectures, and an increasingly common AI-assisted coding round that mirrors real workflows. Data Scientist rounds emphasize product analytics and experimentation—designing tests, diagnosing spend drops and bots, evaluating unconnected content, and writing SQL for multi-account, seller, and vehicle metrics. Machine Learning Engineer questions skew toward recommender and ranking work (place and friend recommendation, sparse-matrix ops, linear-regression derivations, newsfeed dislike models). Data Engineers focus on data modeling, ETL, capacity calculations, reservations/utilization queries, and production SQL/Python tasks. For interview preparation, prioritize timed coding practice, system-design templates, rigorous SQL drills (joins/CTEs/aggregation), clear A/B-testing frameworks, and concise STAR behavioral stories tied to measurable impact.

1.2k Questions 1 Company08.08.2026
Showing 20 results
Role
Meta logo
Meta
Medium
Data Scientist Locked

Investigate Falling Brand-Ad Spend

This question evaluates competency in data analysis, anomaly detection, causal inference, and diagnostic reasoning related to advertising performance,...

Analytics & Experimentation
2
0
54 people solved
Mar 12, 2026
Meta logo
Meta
Easy
Software Engineer

Implement an in-memory database with record locking

Implement an in-memory key–record database that supports basic CRUD on fields plus an exclusive lock per record. You are given a sequence of queries. ...

Coding & Algorithms
9
0
102 people solved
Mar 8, 2026
Meta logo
Meta
Medium
Software Engineer

Merge Two Lists of Non-Overlapping Intervals

You are given two lists of closed integer intervals, a and b. Each interval is represented as a pair [start, end] with start <= end, and it covers eve...

Coding & Algorithms
1
0
13 people solved
Mar 6, 2026
Meta logo
Meta
Medium
Software Engineer

Minimum Round-Trip Flight Cost

You are planning a round trip and want to spend as little as possible on flights. You are given two integer arrays of equal length n: - departure[i] —...

Coding & Algorithms
0
0
5 people solved
Mar 6, 2026
Meta logo
Meta
Medium
Software Engineer AI

Maximum Length of a Word Selection With All Unique Characters

You are given an array of lowercase strings words. Select a subset of these words (zero or more, chosen in any order) and concatenate them. The select...

Coding & Algorithms
0
0
7 people solved
Mar 6, 2026
Meta logo
Meta
Hard
Data Scientist

Write SQL for reply-based recipient metrics

You work on a social product and are given two tables. Assumptions (use these unless you state otherwise): - All timestamps are in UTC. - A “reply” is...

Data Manipulation (SQL/Python)
47
2
437 people solved
Mar 5, 2026
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Meta
Medium
Software Engineer

Construct a BST and read spiral order

The coding round reportedly included two algorithmic tasks: 1. Rebuild a binary search tree from a preorder sequence - You are given an array of di...

Coding & Algorithms
17
0
115 people solved
Mar 4, 2026
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Meta
Medium
Data Scientist Locked

Write SQL for seller and vehicle metrics

This question evaluates proficiency in SQL data manipulation, including joins, distinct counts, grouping and aggregation, filtering by date and catego...

Data Manipulation (SQL/Python)
7
0
81 people solved
Mar 2, 2026
Meta logo
Meta
Hard
Machine Learning EngineerSenior+ AI Locked

Build a Friend Recommender

This question evaluates proficiency in graph algorithms, recommendation system logic, input validation, metric design, and test-driven software implem...

Coding & Algorithms
3
0
46 people solved
Mar 1, 2026
Meta logo
Meta
Hard
Machine Learning EngineerSenior+ AI Locked

Optimize a Fifteen-Sum Card Strategy

This question evaluates algorithmic problem-solving, debugging, simulation-based testing, and strategy optimization using techniques such as search, m...

Coding & Algorithms
6
0
58 people solved
Mar 1, 2026
Meta logo
Meta
Hard
Machine Learning EngineerSenior+ AI Locked

Find Words Containing Other Words

This question evaluates string-processing skills, knowledge of substring matching techniques and supporting data structures, and the ability to analyz...

Coding & Algorithms
1
0
30 people solved
Mar 1, 2026
Meta logo
Meta
Medium
Data Scientist Locked

Assess Group Video Chat Demand

This question evaluates a data scientist's product analytics competencies including causal inference, experiment and questionnaire design, proxy metri...

Analytics & Experimentation
3
0
30 people solved
Mar 1, 2026
Meta logo
Meta
Hard
Software Engineer

Check and infer custom alphabet

You are working with an unknown language that uses a custom alphabetical order, such as ['a', 'd', 'c', 'b', ...]. Implement the following: 1. Check s...

Coding & Algorithms
4
1
67 people solved
Feb 28, 2026
Meta logo
Meta
Medium
Software Engineer

Design a ride-sharing system like Uber

Design a ride-sharing system. Requirements: - Riders request trips with pickup/dropoff. - Drivers send frequent location updates. - Match riders to ne...

System Design
5
0
52 people solved
Feb 25, 2026
Meta logo
Meta
Medium
Software Engineer

Design a nearby places (proximity) service

Design a proximity search service like Yelp/Google Maps. Requirements: - Store places with (place_id, name, lat/lng, category, rating). - Query: “find...

System Design
5
0
44 people solved
Feb 25, 2026
Meta logo
Meta
Medium
Data Scientist

Analyze spend cohort and source shifts

You work on an ads platform. Assume all timestamps are in UTC. Interpret last year as calendar year 2023 and this year as calendar year 2024. Tables: ...

Data Manipulation (SQL/Python)
11
2
80 people solved
Feb 23, 2026
Meta logo
Meta
Medium
Data Scientist Locked

Measure fake account prevalence

This question evaluates a data scientist's competency in fraud measurement, statistical estimation, experimental design, and model evaluation for dete...

Analytics & Experimentation
4
0
42 people solved
Feb 22, 2026
Meta logo
Meta
Medium
Data Scientist Locked

Evaluate an ads algorithm change

This question evaluates competency in experiment design, causal inference, metric selection, product analytics, and evaluation of ad-ranking systems, ...

Analytics & Experimentation
8
0
69 people solved
Feb 22, 2026
Meta logo
Meta
Medium
Data Scientist Locked

Find least active countries

This question evaluates proficiency in SQL-based data manipulation and analytics, focusing on time-based filtering, distinct aggregation, grouping, th...

Data Manipulation (SQL/Python)
4
1
42 people solved
Feb 22, 2026
Meta logo
Meta
Medium
Software Engineer

Find Kth Largest and Tree Ancestors

In a technical phone interview, the candidate was asked two coding problems in the same round: 1. K-th largest element in an array Given an unsor...

Coding & Algorithms
3
0
56 people solved
Feb 22, 2026

Frequently Asked Questions

How difficult are Meta interview questions?
Meta interview questions span a wide difficulty range because they must screen candidates from entry to senior levels across many functions. Expect coding rounds to map to medium-to-hard algorithmic problems that appear in top 100 problem lists for software engineers, and expect data roles to face challenging SQL, experiment diagnosis, and product-analytics problems that require clean metric definitions. Machine learning roles emphasize recommendation and ranking tradeoffs and model complexity, while data engineers encounter large-scale ETL and modeling puzzles. Difficulty scales with level: entry hires see clearer, bounded problems; senior hires face ambiguous tradeoffs and system-wide thinking.
What is Meta's interview process and where do these questions appear?
Meta typically runs a multi-stage process: recruiter screen, one or two technical screens or an online assessment, a full loop of onsite-style interviews, then debrief, committee review, and offer. The full loop mixes coding, system or product design, role-specific technical rounds, and behavioral interviews. Software-engineer candidates spend most time on coding and design; data scientists focus on SQL, experimentation, and product analytics; machine-learning engineers see modeling and recommendation design; data engineers handle SQL, data modeling, and pipeline questions; PMs get product-design and analytics probes. In 2025–2026 some teams pilot AI-enabled coding rounds.
How should I structure a preparation timeline for a Meta interview?
A focused six-week plan works well: weeks one and two cover fundamentals—data structures, algorithms, SQL basics, and experiment design; weeks three and four emphasize timed problem practice, mock phone screens, and role-specific cases (A/B diagnosis for data scientists, model design for MLEs, ETL modeling for data engineers); week five concentrates on system or product design and behavioral storytelling; week six is for full mock loops, timing, and refining communication. Practice with realistic tools, simulate loop pacing, and schedule a debrief after each mock to iterate on clarity, edge-case handling, and time management.
Which technical subtopics are most commonly tested for each role at Meta?
For Data Scientist interviews the recurring technical themes are product-metric definition, diagnosing experiment and spend drops, counting multi-account interactions, SQL for multi-entity metrics, and ranking or recommendation evaluation such as shop ad ranking. Software-engineer questions frequently focus on timestamped state and versioned systems, leaderboards and ranking, maze/graph traversal and tree/array transforms, delimiter and CSV parsing, and scalable search or flight-search style designs. Machine-learning engineers see place and friend recommendation design, sparse-matrix operations, ranking/loss choices, and feed dislike or personalization models. Data engineers repeatedly face entity modeling for feed and booking data, SQL analytics for utilization and reservations, and capacity-aware aggregation challenges.
What standout tips and common pitfalls should I watch for in Meta interviews?
Start interviews by clarifying requirements and expected outputs, then propose measurable success metrics; this prevents misaligned solutions. For coding, think aloud, handle edge cases, state complexity up front, and write a couple of quick tests. In design rounds quantify load, storage, and tradeoffs rather than vague features. Data roles must define metrics, guardrails, and experiment assumptions before jumping to analysis; common pitfalls are ambiguous metric definitions, peeking at tests, and ignoring instrumentation limits. For AI-assisted coding rounds, use the assistant to accelerate boilerplate but validate logic and corner cases yourself. Finish each answer with a concise summary of impact and tradeoffs.

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