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.
As an engineer working on our Distributed Storage team, you will be building our high-scale distributed databases serving time series data throughout the product. You will be working with various distributed sharding strategies towards optimizing scalability and availability, and making low-level improvements which have an outsized impact on Datadog’s overall query performance and scalability.
- Build distributed, high-throughput, time series databases
- Do it in Go and using tools such as LevelDB and RocksDB
- Own meaningful parts of our service, have an impact, grow with the company
- You have a BS/MS/PhD in a scientific field or equivalent experience
- You have significant backend programming experience in one or more languages
- You can get down to the low-level when needed
- You care about code simplicity and performance
- You want to work in a fast, high-growth startup environment that respects its engineers and customers
- You've worked on distributed databases, or maybe built your own
- You've built high scale systems with Cassandra, Redis, Kafka or Numpy
- You have significant experience with Go, Rust or C++
- You have a strong background in stats
Equal Opportunity at Datadog:
Datadog is an Affirmative Action and Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
For more information on how we maintain the privacy of the information you submit as part of your application, please refer to our Applicant and Candidate Privacy Notice.