Datadog Software Engineer interview questions typically focus on practical, production-oriented problem solving: expect live coding that emphasizes clean, efficient implementations; system design that probes scalability, observability, and trade‑offs; and behavioral conversations that assess ownership, collaboration, and impact. What’s distinctive is the company’s emphasis on real-world operational concerns—metrics, monitoring, reliability, and efficient data pipelines—so interviewers evaluate both algorithmic skill and an engineer’s ability to reason about running services at scale. For interview preparation, plan a mix of algorithm practice, end‑to‑end system design rehearsals, and concise storytelling about past projects where you owned outcomes. Prepare concrete examples showing how you diagnosed incidents, reduced latency, or improved observability, and practice coding in the language you’ll use on the call. Expect an initial recruiter screen, one or two timed coding interviews, a system design session, and behavioral/hiring manager rounds; team matching often happens later in the process. Prioritize clarity, trade‑off discussion, and evidence of operational thinking.