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.
Our Logs Storage team owns the logs indexing, analytics, and archival systems underpinning the Datadog logs management application. They build, scale, and operate some of the high-volume data systems that power the growth of our business.
As a Software Engineer for the Logs storage team, you will build and maintain the indexing and analytics pipeline and data store as well as the archival system turning the logs data into actionable insights for our customers. You will build distributed, high-volume, and low-latency systems with a strong focus on availability, resilience and durability. Working closely with our product managers to support our wide range of customers and data, you will build new features as well as scale our systems for our fast-growing business.
- Code (Go and Java) new and existing services to scale out our logs storage systems
- Contribute to the design of the logs storage architecture and systems
- Debug and solve challenging cross-systems issues in production
- Help improve our engineering tooling and practices
- You have been building applications for 2+ years and know the systems you’ve worked on from top to bottom
- You have backend programming experience
- You are passionate about performance
- You have architected, built, and operated distributed systems to solve problems at high scale
- You have a BS/MS/PhD in a scientific field or equivalent experience
- You want to work in a fast-paced, high-growth startup environment that respects its engineers and customers
- You have experience working at high scale on search or IR frameworks like Lucene or analytics databases like Druid
- You understand the inner workings of low-level storage systems
- You have a strong background in statistics
- You have significant experience with Go or a JVM based language