Meta Behavioral & Leadership 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.
"I got asked a hardcore MCM DP question and I saw it on PracHub as well. Solved that question in 5 minutes. Without PracHub I doubt I could solve it in 5 hours. Though somehow didn't get hired, perhaps I guess I solved it too fast? /s"
"Believe me i'm a student here jn US. Recently interviewed for MSFT. They asked me exact question from PracHub. I saw it the night before and ignored it cause why waste time on random sites. I legit wanna go back and redo this whole thing if I had chance. Not saying will work for everyone but there is certainly some merit to that website. And i'm gonna use it in future prep from now on like lc tagged"
"10 years of experience but never worked at a top company. PracHub's senior-level questions helped me break into FAANG at 35. Age is just a number."
"I was skeptical about the 'real questions' claim, so I put it to the test. I searched for the exact question I got grilled on at my last Meta onsite... and it was right there. Word for word."
"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."
"I've used LC, Glassdoor, and random Discords. Nothing comes close to the accuracy here. The questions are actually current — that's what got me. Felt like I had a cheat sheet during the interview."
"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."
"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."
"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."
"Literally just signed a $600k offer. I only had 2 weeks to prep, so I focused entirely on the company-tagged lists here. If you're targeting L5+, don't overthink it."
"Coaches and bootcamp prep courses cost around $200-300 but PracHub Premium is actually less than a Netflix subscription. And it landed me a $178K offer."
"I honestly don't know how you guys gather so many real interview questions. It's almost scary. I walked into my Amazon loop and recognized 3 out of 4 problems from your database."
"Discovered PracHub 10 days before my interview. By day 5, I stopped being nervous. By interview day, I was actually excited to show what I knew."
"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."
"The search is what sold me. I typed in a really niche DP problem I got asked last year and it actually came up, full breakdown and everything. These guys are clearly updating it constantly."
Design a recommendation system from scratch
This question evaluates expertise in recommender systems and related competencies including machine learning-based candidate generation and ranking, d...
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...
Analyze advertiser spend by source
This question evaluates proficiency in data manipulation and analytics using SQL or Python, testing skills such as joins, time-based filtering, cohort...
Resolve Conflicts and Convince Skeptical Stakeholders Effectively
Resolve Conflicts and Convince Skeptical Stakeholders Effectively Scenario You are an IC-level data scientist (IC5-or-below) working on fast-paced, cr...
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...
Troubleshoot a website outage with disk full
This question evaluates operational incident response and systems troubleshooting skills, including understanding of disk/storage behavior, log and me...
How to evaluate new listing notifications?
This question evaluates a data scientist's competency in experimental design, causal inference, metric selection (primary, secondary, guardrail), and ...
Write queries for follows and bookings
This question evaluates the ability to manipulate temporal event logs, enforce bidirectional relational integrity, and implement efficient graph and i...
Design an online auction system
Design an online auction system (eBay-style). Requirements: - Users create auctions with start/end time and starting price. - Users place bids; system...
Write SQL for car rental utilization by city
SQL / Data Query Prompt (Car Rental) You are given four tables: user - user_id location - location_id - city car - car_id - car_size (e.g., compact, m...
Evaluate AI-assisted ad creation
Meta is considering launching an AI-assisted ad creation feature for advertisers. The feature helps advertisers generate ad copy and/or creatives insi...
Troubleshoot a single-node web outage
This question evaluates operational troubleshooting, root-cause analysis, and resilience design skills for a single-node web server, testing a candida...
Build a FastAPI summarization service
Implement a minimal but production-ready FastAPI service for text summarization. Requirements: - Expose an endpoint POST /summarize. - The request bod...
Describe handling intense time pressure
Behavioral & Leadership (Onsite): Thriving Under Time Pressure and Multitasking Prompt Tell me about a time you had to deliver high‑quality work under...
Handle feedback, change pivots, and conflict
Question In the behavioral portion of the Meta Data Scientist screen, answer the following leadership prompts using concrete examples from your own wo...
Evaluate AI-assisted ads creation feature
This question evaluates a data scientist's competence in experimental design, metric selection, causal inference, and balancing business metrics with ...
Design an ad recommendation and ranking system
You are building an ad recommendation/ranking system for a content feed (e.g., short-form videos). At each feed position, you may show either an organ...
Handle conflict and missed delivery deadlines
Answer behavioral questions covering: 1. Conflict: Describe a time you had significant conflict with a teammate/stakeholder. What caused it, what did ...
Implement an in-memory key-field-value DB with TTL
In-Memory DB with TTL + Scan + Backup/Restore Implement an in-memory database storing records by (key, field) -> value with optional TTL. Data model /...
Design a clustered A/B test with spillovers
This question evaluates a data scientist's understanding of cluster-randomized experiments with spillovers, covering causal inference under interferen...