We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale—trillions of data points per day—providing always-on alerting, metrics visualization, logs, and application tracing for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way.
Using a mix of open-source and proprietary applications the Data Engineering Infrastructure team enables engineers at Datadog to build and run thousands of data pipelines per day against petabyte-scale data. If you’re excited by the intersection of big data and building platforms, this is the team for you.
As an engineer for the Data Engineering Infrastructure team, you will design, build, scale, and evolve our data engineering platform, services and tooling. Your work will have a critical impact on all areas of Datadog's business: powering core data pipelines, supporting detailed internal analytics, calculating customer usage, securing our platform, and much more.
- Build a big data platform-as-a-service (PaaS) for Spark, Luigi, Airflow, Kubernetes, and other open-source technologies on AWS and GCP
- Engage other teams at Datadog about their use of the platform to ensure we’re always building the right thing
- Use Datadog products to provide observability for our engineers so they can easily debug, scale, and tune their Spark jobs and data pipelines
- Join a tightly knit team solving hard problems the right way
- You have a BS/MS/PhD in a scientific field or equivalent experience
- You have experience contributing to a software engineering team
- You have experience with a mix of backend programming, operations, and working with data
- You value code simplicity and performance
- You want to work in a fast, high-growth startup environment that respects its engineers and customers
- You have production experience running and operating state-of-the-art data processing frameworks, technologies, and platforms
- You have built and operated data pipelines for real customers in production systems
- You’ve built applications that run on AWS or GCP