Data Engineer - Metrics
- New York, NY
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.
- Build distributed, high-volume data pipelines that power the core Datadog product
- Do it with Spark, Luigi, Kafka and other open-source technologies
- Work all over the stack, moving fluidly between programming languages: Scala, Java, Python, Go, and more
- Join a tightly knit team solving hard problems the right way
- 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 built and operated data pipelines for real customers in production systems
- You are fluent in several programming languages (JVM & otherwise)
- You enjoy wrangling huge amounts of data and exploring new data sets
- You value code simplicity and performance
- You want to work in a fast, high growth startup environment that respects its engineers and customers
- You are deeply familiar with Spark and/or Hadoop
- In addition to data pipelines, you’re also quite good with Kubernetes and cloud technology
- You’ve built applications that run on AWS
- You’ve built your own data pipelines from scratch, know what goes wrong, and have ideas for how to fix it
Is this you? Send your resume and link to your GitHub if available.
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.
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