I applied through an employee referral. The process took 2 months. I interviewed at Meta (Londres, Inglaterra) in Mar 2019
Interview
As it often happens, the interviewer was late about 6 minutes (it was a online call). We had a shared screen and I was given some tables for me to query from.
There was no compiler I could see, meaning that if something wasn't right I couldn't really know unless he would tell me. He did for the first one, and I corrected it but he didn't tell me anything about the second query not being right. I agree that I should've corrected it by taking a second look at it, but since the interviewer didn't point out any mistake in the second query, why should I bother while I very well knew I was under time pressure for further questions.
Interview questions [4]
Question 1
Given a table containing date, post_id, relationship (e.g. Friend, Group, Page), interaction (like, share etc.) and a table containing poster id and post id, calculate: how many likes were made on friend posts yesterday
Tough interview overall—definitely not what I expected. The technical rounds were intense, particularly when they had me design an A/B test for the News Feed ranking algorithm. I had to discuss metrics and sample sizes in detail. Lucky for me, the time I spent on PracHub right before the interview helped me nail that deep-dive question as it mirrored what I practiced. The behavioral questions felt standard but were still challenging. After a whirlwind process, they extended an offer, which I happily accepted.
Interview questions [1]
Question 1
Design an A/B test to evaluate a new ranking algorithm for the Facebook News Feed. Walk through metric selection (engagement, time-spent, MSI, well-being), unit of randomization given network effects between friends, sample size and power calculations, how you'd detect novelty effects vs. true lift, and how you'd handle a guardrail metric regressing while the primary metric is up.
Total 7 rounds: first round for resume screening, second for technical screening, then for on-site virtual with 4 interviews back to back, then hiring manager round after team matching and then salary negotiation with HR
Interview questions [1]
Question 1
Meta’s evaluation rubrics focus heavily on "Product Thinking over Fancy Math". Interviewers want to see if you can operate like a product owner with an analytical mindset, navigating messy scenarios affecting billions of users
The Interview Process is very structured -
First Tech Screening round - 45 mins (usually can extend a bit depending on the interviewer)
- 2 SQL Questions ( Medium to Hard ) - based on Joins
Full Loop - 4 rounds 45 mins each.
- SQL
- Behavioral
- Analytical Execution - stats & prob, A/B testing, case study
- Analytical Reasoning - Case study
Interview questions [1]
Question 1
Questions on Bayes Theorem, Probability distribution, etc.
