Meta Data Engineer Interview Questions
17+ questions from real Meta Data Engineer interviews, reported by candidates.
Round Types
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Questions
Meta | Data Engineer | New Onsite Format
Hi all, I went through a DE onsite with Meta (unsure about level) and apparently the new format for these are considered "full stack DE" vs the previous ETL1, ETL2, Data...
Interview
meta new grad onsite DE interview Behavioural - this went great Full stack 1 - solved everything optimally , it was great Full stack 2 - solved everything optimally, finished...
Facebook | Data Engineer | Menlo Park | Jan 2021
Status: Data Engineer at a Healthcare company Location: Austin, TX Date: January 26, 2021 Contacted by a recruiter on LinkedIn and set up a call for phone screen. Phone screen: It had 10 basic questions:...
Facebook | Data Engineer (Product Analytics) | Seattle | Reject
I appeared for the Data Engineer phone screen interview last week. I had applied for the job on the FB site and got a call from recruiter. Recruiter was very...
Facebook Data Engineer London| Onsite Scheduled
YOE:13+ Current: Technical Architect/Senior DE Referred by Friend. Had an initial call with recruiter where very basic questions were asked: select 1+null, where vs having, union vs union all, left join what happens python:...
Facebook Onsite Data Engineer London: Rejected
YOE: 13+ Current: Technical architect Big data Referred by Friend: There are no materials available to prepare for DE so I focused on the materials shared by FB. Have signed NDA so ony...
Compiling a list of FB DE questions and optimized solutions for everyone to read in one place. Please enter your solutions or any other questions you may have seen before. 1)...
I don\'t see as much entries here for Data Engineer (DE) roles as Software Engineers so posting this to hopefully get things going. Recently completed the facebook assessment for a position...
I\'ve been reading Facebook Data Engineer on-site experiences of people, and most of them were asked to implement a scalable logging service. This was a whiteboard coding question. Would love...
Facebook | Phone | Mismatched sentences & Fill an Array
I\'ve gotten a lot from this community and want to give back. These are questions from my phone screen, for a data engineering role. The key to my success was...
Facebook | Phone | Simple spell checking engine
As per Glassdoor this was asked in recent Data Engineer phone interview. I.e Easy & Expected to be done in < 10 min. I really can\'t think a way to do...
Data Engineer - Facebook
Reached out by a facebook recruiter in linkedin and did the phone screen - basic questions on SQL and python. The phone screen went fine and got scheduled for a...
Facebook Data Engineering Interview - Onsite
I recently got this question in the data engineering on-site interview for position in menlo park. This was part of the data modeling/ System Design interview. The interviewer shared the...
Facebook|Sr Data Engineer|NY, USA|Oct 2020|SQL/Python|Nooffer
No referal, this is for Sr data engineer role, location: NY USA I had phone interview with data engineer. I was able to solve only 3 sql and 3 python SQL Products/ Sales/Promotions...
Facebook | Data Engineer Intern | London | Nov 2020 [Reject]
Status: Post Graduate, MSc CS far from top ones Position: Data Engineer Intern at Facebook Location: London, UK Date: November 11, 2020 HR phone screen (20 minutes): - Behavioral questions - 5 Algorithm question...
Facebook | Phone | Data engineer
Status: Experienced Position: Senior Data Engineer Location: Menlo Park, CA Duration: 1 hour Questions asked Python: 1) find the average length of word in sentence sentence = "Hi my name is Bob" words = sentence.split() print(words) average=1.0* sum(len(word)for...
Position: Data Engineer Given a log file with data like: USER FROM_PAGE TO_PAGE \tA url1 url2 \tA url1 url3 \tB url1 url3 \tA url2 url3 \t... \t... \turl can be string like www.leetcode.com/activity/xyz \t \tReturn the possiblity of any user moving...
What Meta Looks for in Data Engineer Interviews
Meta Data Engineer interviews are calibrated against the level and scope expected of the role. Across 17+ verified candidate reports on LeakCode, the consistent signals interviewers look for: clear problem decomposition before coding, explicit complexity reasoning, structured handling of edge cases, and the ability to articulate trade-offs between two reasonable approaches.
The discriminator between candidates who advance and candidates who do not is rarely the final correctness of the solution. It is the path to the solution: did you ask clarifying questions, did you state your approach before coding, did you handle edge cases without prompting, and did you communicate your reasoning throughout. Reports tagged "no hire" frequently cite a working solution with poor communication; reports tagged "strong hire" cite clear thinking even when the final solution was incomplete.
How To Use This Question Set
Real interview reports are a calibration tool, not a memorization target. Companies update their question pools every 2-4 months; memorizing exact problems risks misleading you when the interviewer uses a variant. The high-leverage use: identify the patterns that appear repeatedly in Meta Data Engineer reports, practice those patterns on similar (not identical) problems, and use the reports to understand the interviewer's typical follow-up depth.
Filter the questions below by round type, difficulty, and recency. Focus first on reports from the past 6-12 months; older reports may reference questions that have since rotated out of Meta's pool. Reports tagged with quantified difficulty (e.g., "medium-hard") are higher-signal than reports without difficulty tags.
Round-by-Round Expectations
Meta Data Engineer loops typically span 4-6 rounds across phone screens and on-site or virtual on-site interviews. The structure varies by company: some run 1 recruiter screen + 1 technical phone + 3-4 on-site rounds; others run 1 recruiter screen + 1 OA + 4-5 on-site rounds. The recruiter screen is logistics and culture-light; the technical phone screen is medium-difficulty coding; the on-site loop covers coding, system design (at L4+ levels), and behavioral rounds.
Each round is designed to surface a specific signal. Coding rounds: correctness, code quality, complexity reasoning, communication. System design rounds: requirements clarification, design judgment, operational thinking. Behavioral rounds: ownership scope, leadership, ambiguity tolerance, conflict navigation. Strong candidates explicitly hit each signal dimension out loud during the round; weak candidates focus only on solving the prompt.
Common Interview Mistakes At This Combination
Reports tagged "no hire" at Meta Data Engineer commonly cite: jumping into code without clarifying requirements, coding silently for 10+ minutes without verbalizing approach, missing edge cases (empty input, single element, very large input, overflow), and producing a working solution that the candidate cannot explain or refactor when probed. Strong candidates avoid these patterns by following a consistent template: clarify, verbalize approach, code with narration, test with examples.
Behavioral and design rounds have their own failure modes. Behavioral: stories that use "we" instead of "I" diluting individual signal, stories with no quantified outcome, defensiveness when probed about failure. Design: not asking clarifying questions, not stating requirements out loud, designing for a single server when the prompt clearly implies scale, ignoring operational concerns (deployment, monitoring, rollback). These show up in roughly half of Meta Data Engineer interview retrospectives on LeakCode.
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