Hey everyone! Just wanted to share that I just passed my first-round interview for a Data Engineer role at Meta. Super pumped but also nervous for the next rounds. Thought I’d drop what they asked me in case it helps someone else prepping!

Interview Format:
Duration: ~45 mins
Interviewer: Seemed like a senior engineer, super chill and direct
Structure: 50% SQL + 50% Data Engineering concepts
Questions They Asked Me:
SQL (Code on shared doc)
Basic SQL Querying – Given a dataset, write a query to pull top-performing products based on revenue.
Joins & Aggregations – Combine user activity with purchase history, calculate total spend per user.
Window Functions – Rank users based on the most recent login per region.
Data Engineering Concepts:
Data Modeling – How would you design a schema for an e-commerce company tracking orders and customer interactions?
ETL vs. ELT – When would you use each, and which would be better for large-scale real-time data processing?
Partitioning & Indexing – Explain how partitioning works in a large fact table and why it's useful.
Scalability & System Design – If we have a daily log file of 100GB, how would you design a system to process and store it efficiently?
My Takeaways:

They love SQL—seriously, brush up on window functions, joins, and performance optimization.
Be concise in explanations, they don’t want textbook answers, just practical thinking.
If you don’t know something, talk through your thought process—they’re looking for problem-solving, not perfection.
Mock interviews are crucial for practicing your explanations effectively. I used an AI mock interview platform to go over key Data Engineering concepts—uploaded a set of custom questions and also practiced with the built-in question bank. Ended up seeing a few similar questions in my actual interview.
I know the next rounds will be even tougher, so if anyone has Meta Data Engineer interview tips, I’m all ears! Also, let me know if you want me to break down my answers to any of these!