About Datadog:
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.
The team:
As an engineer working on the Distributed Caching team, you will build a new high-throughput, low-latency cache that will be critical to much of Datadog’s infrastructure. As the solution is adopted and matures, you’ll continue to help scale it to meet Datadog’s growing needs. The cache, an in-memory distributed key-value store, will be accessed hundreds of millions of times per second by different internal services.
Locations:
We are a globally distributed team with US Offices in New York (HQ), Boston, Denver, San Francisco, and South Bay and International Offices in Paris, Dublin, London, Madrid, the Netherlands, and Singapore. About 33% of our engineering team are remote.
Datadog values people from all walks of life. We understand that not everyone will meet these requirements on day one. If you’re passionate about building large distributed systems and want to grow these skills but don’t meet all of these qualifications, we encourage you to apply.
You will:
Requirements:
Bonus points:
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.
Your Privacy:
Datadog (NYSE: DDOG) is a prominent global SaaS provider that uniquely balances growth and profitability. It offers cloud-scale monitoring and security by combining metrics, traces, and logs within one platform.
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