Meta Data Engineer Interview Questions (2026)

Landing a Data Engineer role at Meta requires targeted preparation. Meta uses a structured interview process with a coding round, system design round, and behavioral round. Coding interviews focus on algorithms and data structures with emphasis on optimal solutions. System design questions test your ability to build scalable social and real-time applications. Behavioral questions focus on your ability to move fast and create impact. This guide covers the most frequently asked questions and insider tips to help you succeed in your Meta Data Engineer interview.

About the Meta Interview Process

Meta interviews combine coding assessments with system design and behavioral questions focused on impact and moving fast.

Meta uses a structured interview process with a coding round, system design round, and behavioral round. Coding interviews focus on algorithms and data structures with emphasis on optimal solutions. System design questions test your ability to build scalable social and real-time applications. Behavioral questions focus on your ability to move fast and create impact.

Why Meta Data Engineer Interviews Are Different

Meta Data Engineer interviews differ from standard Data Engineer interviews in several key ways. The company has a unique interview culture, specific evaluation criteria, and expects candidates to demonstrate alignment with their values and mission. Understanding these differences gives you a significant advantage over other candidates.

Top 10 Data Engineer Interview Questions at Meta

1. Meta interviewers often ask: Explain the difference between ETL and ELT.
2. Expect this at Meta: How would you design a data pipeline for real-time analytics?
3. Meta interviewers often ask: What is the difference between a data lake and a data warehouse?
4. Expect this at Meta: Describe your experience with Apache Spark or similar frameworks.
5. At Meta, you might be asked: How do you handle data quality and validation?
6. Meta interviewers often ask: What is data partitioning and why is it important?
7. Expect this at Meta: How do you optimize query performance on large datasets?
8. A common Meta interview question: Describe a complex data pipeline you have built.
9. A common Meta interview question: How do you handle schema evolution in data pipelines?
10. Expect this at Meta: What tools do you use for data orchestration?

Meta-Specific Preparation Tips for Data Engineer Candidates

• Practice medium to hard coding problems focusing on optimal time and space complexity
• Study system design for social networks, messaging, and real-time feeds
• Prepare stories demonstrating bold decisions and moving fast with impact
• Be ready to discuss how you handle disagreements and drive consensus
• Practice coding on a shared screen or whiteboard environment

General Data Engineer Interview Tips

• Be proficient in SQL and at least one programming language
• Understand distributed computing concepts
• Know common data modeling techniques
• Be ready to discuss data governance and compliance

Preparation Timeline for Meta Data Engineer Interviews

• 4 weeks before: Research Meta culture, recent news, and the specific team you are applying to.
• 2-3 weeks before: Practice technical questions daily and prepare behavioral stories using the STAR method.
• 1 week before: Do full mock interviews with HireFlow AI simulating Meta interview style.
• Day before: Review your notes, prepare questions for the interviewer, and get a good night of rest.

Practice Meta Data Engineer Interview with HireFlow AI — our AI adapts to Meta's interview style and gives real-time feedback.