Meta Interview Questions

Meta Data Manipulation (SQL/Python) 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
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Meta
Medium
Data Scientist

Find the most-used app

You work on Oculus app engagement analytics. Tables user_activity - user_id (BIGINT) - date (DATE) — day of activity (assume UTC unless otherwise spec...

Data Manipulation (SQL/Python)
4
0
31 people solved
Aug 17, 2025
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Meta
Medium
Data Scientist Locked

Define and estimate prevalence of unhealthy users

This question evaluates a data scientist's ability to operationalize an "unhealthy user" metric and compute its prevalence from session duration and d...

Analytics & Experimentation
3
0
35 people solved
Aug 17, 2025
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Meta
Medium
Software Engineer

Implement sparse vector dot product

Question Design a SparseVector class for vectors of integers in which most entries are zero, and support an efficient dot product between two such vec...

Coding & Algorithms
2
0
39 people solved
Aug 14, 2025
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Meta
Medium
Software Engineer

Compute BST range sum

Given the root of a binary search tree and two integers low and high (inclusive), compute the sum of values of all nodes with low <= val <= high. Prov...

Coding & Algorithms
3
0
29 people solved
Aug 14, 2025
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Meta
Medium
Software Engineer

Solve windowed duplicates and target expression

1) Windowed duplicate check: Given an integer array nums and an integer k, determine whether there exist indices i and j such that nums[i] == nums[j] ...

Coding & Algorithms
2
0
31 people solved
Aug 13, 2025
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Meta
Medium
Software Engineer

Solve tree traversal and interval merging tasks

Part A — Column-wise Binary Tree Grouping: You are given the root of a binary tree. Group nodes by vertical column index, where the root has column 0,...

Coding & Algorithms
4
0
36 people solved
Aug 13, 2025
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Meta
Medium
Software Engineer

Validate a simplified numeric string

Implement isValidNumber (s) that returns true if and only if the ASCII string s represents a valid number under these simplified rules: - Optional lea...

Coding & Algorithms
5
0
59 people solved
Aug 12, 2025
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Meta
Medium
Software Engineer

Remove runs of length at least k

Given a string s and an integer k (k >= 2), repeatedly remove every maximal contiguous group of the same character whose length is at least k, deletin...

Coding & Algorithms
2
0
23 people solved
Aug 12, 2025
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Meta
Medium
Machine Learning EngineerSenior+

Solve matrix components, median, and traversals

1) Binary matrix component: Given an m x n grid of 0s (background) and 1s (objects), return the size of the largest connected component where connecti...

Coding & Algorithms
4
0
51 people solved
Aug 11, 2025
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Meta
Hard
Data Scientist Locked

How would you measure shop-ads promotion success?

This question evaluates a data scientist's competency in metrics design, experimental evaluation, and causal inference for ads ranking systems, includ...

Analytics & Experimentation
1
0
26 people solved
Aug 10, 2025
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Meta
Medium
Software Engineer

Sort a string by custom order

Sort a string by custom order Given a priority string P of distinct characters and a text string S, reorder S so that all characters appearing in P co...

Coding & Algorithms
3
0
39 people solved
Aug 7, 2025
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Meta
Medium
Software Engineer

Decide palindrome within k deletions

Decide palindrome within k deletions Given a string s and integer k, decide whether s can be transformed into a palindrome by deleting at most k chara...

Coding & Algorithms
1
0
22 people solved
Aug 7, 2025
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Meta
Medium
Software Engineer

Find power-of-two subarrays within sum range

Find power-of-two subarrays within sum range Given an integer array nums and an integer k, find all subarrays whose length is a power of two and whose...

Coding & Algorithms
3
0
29 people solved
Aug 7, 2025
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Meta
Medium
Software Engineer

Compute binary tree diameter

Compute binary tree diameter Given the root of a binary tree, compute the tree's diameter defined as the maximum number of edges on any path between t...

Coding & Algorithms
4
0
43 people solved
Aug 7, 2025
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Meta
Medium
Software Engineer

Find buildings with rightward view

Find buildings with rightward view You are given an array of building heights aligned along a street that faces the ocean to the right. Return the ind...

Coding & Algorithms
3
0
25 people solved
Aug 7, 2025
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Meta
Medium
Data Engineer

Demonstrate behavioral competencies

Demonstrate behavioral competencies Behavioral Interview Prompt: Prepare STAR Stories Context You are preparing for an onsite Behavioral & Leadership ...

Behavioral & Leadership
4
0
38 people solved
Aug 4, 2025
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Meta
Medium
Software Engineer

Count uniques in sparse sorted array

Question A sorted array contains many duplicates but only a very small number of distinct values. Design an algorithm that counts how many unique numb...

Coding & Algorithms
29
0
10 people solved
Aug 4, 2025
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Meta
Medium
Software Engineer

Solve grid shortest path and robot cleaning

Question LeetCode 1091. Shortest Path in Binary Matrix; LeetCode 489. Robot Room Cleaner https://leetcode.com/problems/shortest-path-in-binary-matrix/...

Coding & Algorithms
3
0
39 people solved
Aug 4, 2025
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Meta
Medium
Data Engineer

Validate carpool capacity

Question LeetCode 1094. Car Pooling – Given trips[i] = [numPassengers, start, end] and an integer capacity, return true if the vehicle can fulfill all...

Coding & Algorithms
5
0
67 people solved
Aug 4, 2025
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Meta
Medium
Data Engineer

Recommend friends-of-friends

Question Given a dictionary such as {A:[B,C], B:[C,D], C:[E]}, return for a user U all people followed by U’s followees but not already followed by U....

Coding & Algorithms
3
1
65 people solved
Aug 4, 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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