Meta Data Manipulation (SQL/Python) 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.

"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."
Analyze Conversation Engagement and Reaction Usage Effectively
messages +-----------+--------+----------+--------------+---------------------+ | messageid | sender | receiver | has_reaction | timestamp |...
Uncover User Needs for Group Calling Effectively
Scenario You are the product analyst for a messaging platform planning to introduce a group-calling capability. You need to understand user needs, ben...
Design an e-commerce price tracking service
Design a backend system similar to popular price-tracking sites that monitor product prices on large e-commerce platforms (for example, a site that tr...
Compute posterior fake probability using Bayes' rule
A platform runs an automated detector to flag fake accounts. - Prior probability an account is fake: \(P(F)=0.02\). - True positive rate (sensitivity)...
Validate in-post restaurant recommendations via experiment
Evaluate In‑Post Restaurant Recommendations: Metrics and Experiment Design Context You are evaluating a new feature that surfaces restaurant recommend...
Design and critique teen-parent impact experiment
Causal Impact of Parental Registration on Teen Outcomes Meta plans to let parents register and link to their teen’s account. Leaders are concerned abo...
Write SQL for daily chats and fast replies
You are given a messaging events table that records one row per message sent. Schema - messages( date DATE, -- calendar date of event (UTC) ts TIMES...
Evaluate and prioritize Facebook Groups
Analytics & Experimentation: Facebook Groups Context: You are evaluating how to measure and improve Facebook Groups. Assume access to standard product...
Apply reinforcement learning to product decisions
Session‑level recommendations have stateful effects and feedback loops affecting long‑term retention. a) Formulate the problem as an MDP (state, actio...
Handle novelty and residual effects
Experiment design under novelty-decay and residual (carryover) effects Context You are testing a new UI that creates a novelty spike that decays over ...
Estimate variance for ratio metrics
KPI Variance via Delta Method and Inference Choices for ARPU Context You run experiments where each arm produces aggregate totals per analysis unit (e...
Design experiments under network interference
A/B Test Design for Search-Ranking in a Two-Sided Marketplace with Interference Context You need to evaluate a change to the search-ranking algorithm ...
Design robust group size limiting for calls
Design the admission-control and enforcement algorithm to limit group-call size under real-world race conditions. Constraints: multiple SFU edges in m...
Define composite success for search and test it
A new search feature is evaluated with two binary labels per query: relevancy=1/0 and accuracy=1/0. 1) Propose a composite success metric that uses th...
Clarify scope and align to mission
Clarify and Align: New Google Maps Feature to Boost Group Page Engagement Context (Completed) Assume "Group pages" are shared spaces in Google Maps wh...
Choose ML metrics under asymmetric costs
Binary Classifier With Asymmetric Costs: Fraud vs. Cancer Context: You own a production binary classifier and must make product/ML decisions under asy...
Define metrics and design experiments for notifications
Analytics/Experimentation Case: "Your friend is attending a local event—join them?" You are evaluating a proposed notification: "Your friend is attend...
Increase posts receiving comments via experimentation
Increase the Share of Posts That Receive a Meaningful Comment You are a data scientist for a consumer social app with posts and comments. Your goal is...
Calculate posts per DAU by country today
Given two tables: - user_activity(user_id INT, activity_date DATE, country STRING, dau_flag TINYINT CHECK(dau_flag IN (0,1))) - composer(user_id INT, ...
Design experiment with network and novelty effects
Experiment Design: New Calling Feature with Network Interference and Novelty Effects Context: You are launching a new calling feature on a large socia...