Meta Interview Questions
Practice 1,129 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.
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"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."
Ensure Effective Teamwork Amid Conflicting Stakeholder Opinions
Behavioral: Cross-Functional Collaboration, Miscommunication, and Conflict Handling Context You are interviewing for a Data Scientist role in an onsit...
Assess Cultural Fit and Problem-Solving in Reality Labs Role
Behavioral and Leadership Interview Prompts (Data Scientist, Reality Labs) Context The hiring manager wants to assess cultural add, collaboration styl...
Analyze Social Media Engagement with SQL Queries
info_stream_views +----------+---------+-----------+-------------------------+-----------------------+------------+ | view_id | post_id | viewer_id |...
Resolve Ties for Top-10 Users in SQL Query
Oculus_Scores +---------+-------+ | user_id | score | +---------+-------+ | u1 | 95 | | u2 | 92 | | u3 | 90 | | u4 | 90 ...
Determine Success Metrics for Instagram Video-Call Feature
Instagram Group Video-Call MVP: Defining Success and Metrics Context You are the data scientist responsible for evaluating the group video-call MVP on...
Choose Randomization Unit and Mitigate Network Effects
A/B Test Design for a New Messenger Feature with Network Effects Context You are designing an A/B test for a new Messenger feature in a social messagi...
Identify Shops with Low Weekly Visibility Rates
SHOP_VISIBILITY +-----------+---------+------------+---------+ | shop_id | user_id | view_date | visible | +-----------+---------+------------+----...
Analyze Video View Distribution: Mode, Median, Mean Comparison
Scenario You are analyzing user engagement on a short-video sharing product. The team needs statistical insights into how views and shares behave acro...
Compare Instagram and Facebook Stories Using Key Performance Metrics
Scenario You are a data scientist tasked with quantitatively comparing the success of Instagram Stories versus Facebook Stories. Question 1. Define wh...
Analyze Recent User Activity from Video Call Logs
video_calls caller | recipient | ds | call_id | duration 123 | 456 | 2019-01-01 | 4325 | 864.4 032 | 789 | 2019-01-01 | 9395 | 263.7 456 | 032 | 2019-...
Analyze Mobile Promo Orders with SQL Query and Metrics
orders +-----------+---------+--------------+------------+-----------+----------+ | order_id | user_id | order_amount | order_date | is_mobile | is_p...
Influence Stakeholders for Product Decision at Meta
Behavioral: Influencing Stakeholders To Drive a Product Decision Scenario Cross-functional product development at Meta often requires influencing with...
Compute Effective Reads with SQL and Python Streaming
post_read_events +----------+---------+-----------+---------+--------------------+---------------------+---------------------+ | event_id | user_id | ...
Design Metrics to Track and Analyze Spam Impact
Scenario A messaging product team wants to reduce spam without harming normal user experience. You do not have access to a ground-truth spam classifie...
Define and Measure Effective Read on Newsfeed
Designing an "Effective Read" Metric for a Newsfeed Scenario You are tasked with defining and measuring an "effective read" for posts in a social news...
Determine User Demand for New Video-Calling Feature
Analytics Design: Demand Sizing, Evaluation Metrics, and Trade-offs for a New Video-Calling Feature Context (Assumptions to Make the Task Self-Contain...
Analyze Top Call Initiators and Active French Video Callers
calls +---------+-----------+-------------+---------------------+---------+-----------+ | call_id | caller_id | receiver_id | call_start_time | co...
Analyze Ad CTR and Convert Transactions to USD
AdsImpressions +-----------+---------+------------+--------+-----------+ | user_id | ad_id | impressions| clicks | event_dt | +-----------+------...
Identify Features for Fake News Detection on Facebook
Design a Machine-Learning System to Flag Fake News on Facebook Scenario An increase in fake news has been detected on the platform. You are asked to d...
Calculate Expected Comments and Confidence Interval Analysis
Scenario You are analyzing the distribution of comment counts per post for a social platform feature over a fixed time window. Let X be the random var...