Real, anonymous reports from people who interviewed for Data Engineer at Amazon, newest first and distilled into what to expect across the loop.
After a recruiter outreach, I ended up with a fairly direct sequence: a phone screen where SQL and Python questions came up, then a loop-style technical process with a couple of engineering-focused interviews. The phone screen felt easy-to-medium overall, and the questions were mostly about being able to work through SQL queries and reason about a few Python tasks.
My process moved quickly into high-intensity technical rounds. I had two back-to-back interview sessions, each about an hour, and both felt tough in a very similar way: live coding problems that pushed me to think clearly under time pressure. The first round centered on SQL, including one hard SQL problem I had to work through live. The second round shifted to Python with another hard live coding task, and it still stayed tightly connected to how I reasoned rather than only whether the final answer was correct.
The interview process typically begins with a recruiter call, followed by an online assessment and a series of technical rounds, often culminating in behavioral interviews that incorporate Amazon's leadership principles. Candidates should expect a structured flow that moves quickly through these stages, with performance in early assessments influencing progression.
Candidates will face multiple technical interviews focusing on SQL and Python, with questions ranging from basic to hard difficulty. Expect to solve live coding problems while explaining your thought process, and be prepared for a mix of practical coding tasks and theoretical questions about data engineering concepts.
SQL is a central theme throughout the interviews, with questions covering joins, window functions, and recursive CTEs. Candidates should also be ready to discuss data modeling, ETL processes, and how they would structure data workflows, as these topics are heavily evaluated.
Behavioral questions aligned with Amazon's leadership principles are integrated into technical rounds, requiring candidates to provide examples from their past experiences. It's important to articulate your reasoning and decision-making process in a way that reflects these principles.
Overall, the interview difficulty is described as moderate to difficult, with many candidates feeling the pressure of time constraints during live coding sessions. Maintaining composure and clear communication under pressure is crucial to performing well.
Candidates often reflect on the need for deeper preparation in SQL and Python, as well as the importance of being able to explain their reasoning clearly. Many wish they had practiced more under timed conditions to better handle the pressure of the interviews.