Meta Interview Questions

Meta Analytics & Experimentation Interview Questions

Practice 1,159 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 Company07.06.2026
Showing 20 results
Role
Meta logo
Meta
Easy
Software EngineerSenior+

Design an online auction system

Design a scalable online auction service. Users can: - Create an auction (item info, start/end time, reserve price optional). - Place bids while the a...

System Design
13
0
174 people solved
Mar 11, 2026
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Meta
Medium
Software EngineerSenior+ AI

Handle Cross-Team Alignment and Mistakes

The behavioral round focused on three prompts: 1. How do you align requirements across teams? 2. What is the biggest mistake you have made at work? 3....

Behavioral & Leadership
5
0
46 people solved
Apr 8, 2026
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Meta
Medium
Data Scientist

Describe leadership and inclusion examples

Prepare strong behavioral answers for the following prompts: - Tell me about a breakthrough project you led or meaningfully influenced. - Tell me abou...

Behavioral & Leadership
2
0
45 people solved
Feb 22, 2026
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Meta
Easy
Software Engineer

Implement four coding challenges

You are asked to solve the following four independent coding problems. --- 1) Block Placement Simulator (Tetris-like) You have an empty n x m grid (ro...

Coding & Algorithms
8
0
80 people solved
Feb 8, 2026
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Meta
Hard
Data Scientist

How would you evaluate stolen-post detection?

You are interviewing for a Meta DSA (product analytics / data science) role. The product team is launching a new Stolen Post Detection algorithm that ...

Analytics & Experimentation
110
2
1034 people solved
Mar 5, 2026
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Meta
Medium
Machine Learning Engineer

Solve linked list, tree, and grid problems

Problem A — Find cycle entry in a singly linked list You are given the head of a singly linked list. The list may contain a cycle. - Return the node w...

Coding & Algorithms
15
0
104 people solved
Dec 15, 2025
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Meta
Medium
Software Engineer

Describe difficult project, conflict, and PM collaboration

Behavioral round (15 minutes) Answer the following prompts using concrete examples from your experience. 1. Most difficult project - Describe the m...

Behavioral & Leadership
4
0
65 people solved
Dec 15, 2025
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Meta
Medium
Software Engineer

Return Binary Tree Nodes in Vertical Order

Return Binary Tree Nodes in Vertical Order A binary tree has nodes numbered from 0 through n - 1, with node 0 as the root. Arrays left and right conta...

Coding & Algorithms
0
0
11 people solved
Mar 2, 2026
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Meta
Medium
Software Engineer

Resolve a cd Path Against the Current Directory

Resolve a cd Path Against the Current Directory Implement path resolution for a simplified Unix-like cd command. cwd is a normalized absolute path. ar...

Coding & Algorithms
0
0
11 people solved
Mar 2, 2026
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Meta
Hard
Data Engineer

Design batch and streaming ETL architecture

Design batch and streaming ETL architecture System Design: End-to-End Data Platform for Product Analytics (Batch + Near-Real-Time) Context Design a sc...

System Design
66
0
510 people solved
Jul 15, 2025
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Meta
Medium
Software Engineer

Find top-K frequent elements in a stream

You receive a large stream of items (e.g., integers or strings) that may not fit in memory. Design an algorithm that can return the top K most frequen...

Coding & Algorithms
8
0
79 people solved
Feb 25, 2026
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Meta
Medium
Software Engineer

Describe proudest project and cross-team work

Behavioral prompts included: 1. Describe the project you are most proud of. 2. Describe a time you worked across teams to deliver a result. For each, ...

Behavioral & Leadership
3
0
52 people solved
Mar 12, 2026
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Meta
Easy
Product Analyst

Explain a project’s impact and product thinking

A Head of Product asks: 1. Pick one analytics/data science project you led end-to-end. 2. What was the product problem and why did it matter? 3. What ...

Behavioral & Leadership
15
0
107 people solved
Feb 22, 2026
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Meta
Hard
Machine Learning Engineer

Design a scalable MoE pretraining pipeline

Design a Large-Scale MoE Pretraining Pipeline (Bilingual LLM, 1T Tokens, 256×A100-80GB) Context You are designing a pretraining pipeline for a decoder...

ML System Design
20
0
157 people solved
Sep 6, 2025
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Meta
Medium
Software Engineer

Design a Real-Time Trending Hashtags System

Design the backend system that detects and serves trending hashtags from posts on a large social network (Facebook-scale). The service continuously in...

System Design
1
0
15 people solved
Mar 6, 2026
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Meta
Medium
Software EngineerSenior+

Design Queue And Taxi Matching Services

Answer both independent system design prompts. For each one, clarify requirements, propose APIs, describe core data models, explain the architecture, ...

System Design
2
0
29 people solved
Apr 9, 2026
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Meta
Medium
Software Engineer

Implement BFS-based maze solver

Maze Printing and BFS Solver You are given a 2D grid representing a maze. Each cell of the grid is one of: - '#' – wall (cannot be passed) - '.' – emp...

Coding & Algorithms
32
0
318 people solved
Dec 7, 2025
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Meta
Medium
Software Engineer

Design a Scalable Post, Feed, and Search Service

Design a Scalable Post, Feed, and Search Service Design a social-post service with three core capabilities: a user can publish a text post, retrieve a...

System Design
1
0
11 people solved
Mar 2, 2026
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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
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Meta
Medium
Software Engineer

Design a distributed job scheduler

Question Design a distributed job scheduler that can run background jobs at specific times or on recurring schedules (similar to cron but scalable and...

System Design
8
0
56 people solved
Dec 8, 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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