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Join Datadog's Data Platform Experience team as a Staff Engineer to shape how engineering teams build, operate, and evolve products on the Observability Data Platform. This role combines deep distributed systems expertise with technical leadership across multiple teams, influencing platform strategy while remaining hands-on in code.
You will lead strategic engineering initiatives that improve how product teams build and operate services on the platform. Key responsibilities include designing and building scalable platform capabilities for cost intelligence (cloud cost allocation, trend analysis, optimization recommendations), developing operational intelligence and self-service tooling to help teams understand platform health and troubleshoot incidents, and driving reusable platform services that increase engineering autonomy while reducing operational complexity.
You'll provide technical leadership across teams by influencing architecture, mentoring engineers, and raising engineering standards through hands-on contributions. You'll participate in the team's on-call rotation and continuously improve platform reliability, observability, and operational excellence.
Ideal candidates have experience designing and building large-scale SaaS or cloud platforms with deep distributed systems expertise. You should have strong software architecture and system design skills, proven success leading complex technical initiatives across multiple teams, and a platform engineering mindset focused on building reusable capabilities. Backend technology experience with Java and Go, plus distributed infrastructure knowledge (Kafka, Kubernetes) is expected. Experience with observability platforms, internal developer platforms, operational tooling, or AI-powered engineering workflows is beneficial.
Datadog operates as a hybrid workplace to support work-life harmony. The company values diverse backgrounds and encourages applications from those passionate about technology even if you don't meet every qualification on day one.
