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
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Meta
Easy
Data Scientist Locked

Determine if users need a new feature

This question evaluates a data scientist's competency in product analytics, causal inference, experiment design, metric definition, instrumentation, a...

Analytics & Experimentation
2
0
32 people solved
Oct 11, 2025
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Meta
Medium
Software Engineer

Design a real-time ad impression aggregator

Design an ads impression aggregator service with the following requirements: - The system ingests a high-volume stream of impression events (each even...

System Design
3
0
32 people solved
Oct 2, 2025
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Meta
Medium
Machine Learning Engineer

Implement bounds, minimum, pathfinding, and moving average

Solve the following data-structures problems: ( 1) Given two sorted integer lists A and B, merge them into a single non-decreasing array. Then, for a ...

Coding & Algorithms
6
0
49 people solved
Sep 6, 2025
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Meta
Medium
Data Engineer

Solve library SQL and Python tasks

You are given a library domain. Assume these tables: - books(book_id, author_id, title) - authors(author_id, name) - copies(copy_id, book_id, conditio...

Data Manipulation (SQL/Python)
0
2
4 people solved
Sep 6, 2025
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Meta
Medium
Data Engineer

Find customer with max rentals in consecutive weeks

You are given a table purchases(customer_id INT, purchase_date DATE, rented_copies INT). Consider only dates in calendar year 2024. Define a full week...

Data Manipulation (SQL/Python)
0
2
5 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer

Find shortest path and compare BFS vs DFS

Given an unweighted graph (directed or undirected), explain how to find the shortest path between two nodes without writing code. Describe the algorit...

Coding & Algorithms
5
0
51 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer

Demonstrate communication and teamwork

Behavioral and Communication Interview (Software Engineer Onsite) Context: You are a software engineering candidate. Answer concisely using STAR (Situ...

Behavioral & Leadership
2
0
30 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer

Compute vertical order of a BST

Compute the vertical order traversal of a binary search tree. Define coordinates so the root is at column 0, row 0; the left child is (col−1, row+ 1) ...

Coding & Algorithms
2
0
40 people solved
Sep 6, 2025
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Meta
Medium
Software EngineerSenior+

Set up a Python interview environment

You can use AI coding tools. Prepare a clean laptop for a Python-based onsite and explain your steps: ( 1) Install pyenv and set up a project-specific...

Data Manipulation (SQL/Python)
10
0
76 people solved
Sep 6, 2025
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Meta
Hard
Software EngineerSenior+

Design a content processing service

System Design: High-Throughput Content Processing Service Context Design a content processing and moderation service for a large-scale media app. Cont...

System Design
4
0
47 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer

Compute max profit from single stock trade

Given an array prices where prices[i] is the stock price on day i, compute the maximum profit achievable with at most one transaction (one buy and one...

Coding & Algorithms
1
0
23 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer

Implement string dedup and mirror tree traversal

- String cleanup with group deletions (LeetCode-inspired): Given a string s consisting of lowercase letters, repeatedly delete any maximal contiguous ...

Coding & Algorithms
1
0
27 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer

Compute longest rising path in a grid

Given an m×n grid of integers, find the length of the longest path where each step moves up, down, left, or right to a strictly larger value. Return t...

Coding & Algorithms
3
0
43 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer

Optimize flight costs and find grid path

1) Given two integer arrays D and R of equal length n, where D[i] is the cost to depart on day i and R[j] is the cost to return on day j, choose indic...

Coding & Algorithms
4
0
31 people solved
Sep 6, 2025
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Meta
Hard
Software Engineer

Design input validation and error handling

Design Task: API, Validation, and Error Handling for a Top-K Frequency Service Context Design a production-grade service that, given an array of eleme...

System Design
4
0
49 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer

Compute top-N outgoing spenders

Add a feature to report the top N accounts by total outgoing payments across both immediate pays and scheduled payments. Implement: List<String> topNS...

Coding & Algorithms
3
0
24 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer

Solve parsing, counting, ranges, and window problems

Solve the following four algorithm problems: 1) Expression evaluator with + and : Given a string s containing non-negative integers, '+' and '' operat...

Coding & Algorithms
2
0
27 people solved
Sep 6, 2025
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Meta
Hard
Software Engineer

Design an online auction platform

System Design: Real-Time English Auction Platform Goal Design an online auction platform that supports English-style auctions with: - Reserve price - ...

System Design
10
0
80 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer

Reverse sublist between equal-value nodes

Given the head of a singly linked list and a target value v that appears at least twice, reverse the sublist starting at the first node with value v a...

Coding & Algorithms
4
0
39 people solved
Sep 6, 2025
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Meta
Hard
Software Engineer

Handle invalid input at system level

Design: Validation and Error Handling for a Top-K Frequency API Context You are designing a REST endpoint that computes the top-K most frequent values...

System Design
1
0
33 people solved
Sep 6, 2025

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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