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:

The Revenue Data Engineering Teams designs, builds and runs the data pipelines and helper systems to accurately and timely manner quantify our customers’ usage across all Datadog products. This team is at the leading edge of any new product we release.

The opportunity:

As a Data Engineer within the Revenue & Growth group, you will work with Spark and big data tooling to build highly reliable, verifiably-accurate data processing pipelines for a large scale mission-critical process. This team ingests the full firehose of data we receive each day - literally trillions of data points and petabytes of data.

You will:

• Build distributed, high-volume data pipelines that power this core product
• Use Spark, Luigi and other open-source technologies
• Work across the stack, moving fluidly between programming languages: Scala, Python and more
• Join a tightly knit team solving hard problems the right way
• Own meaningful parts of our processing infrastructure, have an impact, grow with the company

Requirements:

• 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

Bonus points:

• You are deeply familiar with Spark, Hadoop and similar frameworks
• In addition to data pipelines, you’re also familiar with Kubernetes and cloud technology
• You’ve built your own data pipelines or data intensive applications from scratch, know what goes wrong, and have ideas for how to fix it