Real, anonymous reports from people who interviewed for Data Engineer at Meta, newest first and distilled into what to expect across the loop.
I went through a recruiter + timed SQL/Python screen, then an onsite loop centered on product-style full-stack cases and an ownership/behavioral round.
I went through a lighter-feeling process where the technical parts were manageable, but the later rounds emphasized situational judgment and how I think under pressure.
The interview process typically begins with a recruiter screen lasting 20-60 minutes, focusing on background, role fit, and basic technical questions. This step is crucial for setting expectations and understanding the candidate's motivations.
Candidates undergo a timed technical screen that includes SQL and Python questions, often structured as multiple-choice or coding problems. The emphasis is on accuracy and speed, with many candidates noting the importance of completing as many questions as possible within the time limit.
The onsite loop consists of multiple rounds, including technical and behavioral interviews, often structured around product case studies or data modeling tasks. Candidates should be prepared to demonstrate both technical skills and their approach to ownership and collaboration.
Later rounds often focus on behavioral and situational judgment questions, assessing how candidates handle conflict, pressure, and decision-making. Effective communication and situational awareness are key to success in these rounds.
Candidates report a high level of difficulty and time pressure throughout the process, particularly during technical assessments. Success hinges on managing time effectively while maintaining accuracy in responses.
Candidates suggest focusing on SQL and Python fundamentals, practicing under timed conditions, and being ready to explain thought processes succinctly. Understanding the importance of pacing and clarity in communication can also improve performance.