I originally applied to a Backend Generalist role in Paris, but midway through the process I pivoted and ultimately accepted a position as an Engineering Manager. My interview experience at Datadog was well structured but role-specific, designed to assess both technical depth and cultural fit across several stages. Because of the pivot, I went through more rounds than a typical candidate, but the process remained clear and consistent throughout.
After I applied, I received an email from a recruiter who was by far one of the best recruiters I’ve met in my ~15-year career. He provided clear instructions on what to prepare before each stage, and it was very apparent that Datadog invests heavily in its recruitment process, especially for the Paris branch. For each round you’re given preparation materials: for coding and system design, they share a short list of topics to brush up on, some of which are easily found online and others that require deeper research. I focused on the most probable questions relevant to the role. For the non-technical rounds, you’re given example questions along with guidelines that suggest using the STAR format, which helped frame answers clearly.
One of the unique aspects of Datadog’s process is the transparency of feedback. After each interview you receive structured notes, and during the “virtual on-site” (a series of several back-to-back interviews), you’re given feedback at the end that outlines positives and also highlights areas to improve. It’s a constructive process that I found rare compared to other companies.
Once all interviews are complete, a hiring committee reviews the entire process and decides whether to move forward. From there, you enter team matching, where you meet a few potential teams in short calls (I’d recommend 45 minutes instead of the standard 30) to ask questions and gauge fit. After you’ve met with a few teams, you select the one you’d like to join, and the team must also select you. Once both sides agree, you move into the offer stage.
