Data Engineer - Internal Analytics Platform

    • New York, NY

About Datadog:

At Datadog, we’re on a mission to build the best monitoring platform in the world. We operate at high scale—trillions of data points per day—and high availability, providing always-on alerting, visualization, and tracing for our customers' infrastructure and applications around the globe.

The team:

We are building a first-class Internal Analytics team composed of Data Engineers and Data Analysts. If you’re excited to work on a fast-moving team with cutting-edge open-source data collection, transformation and analysis tools, we want to meet you.


You will:

  • Collect data from a wide range of sources: AWS S3, Redshift, PostgreSQL, and various APIs
  • Build data ETL pipelines using Spark, Luigi and other open-source technologies, with programming languages like Scala, Python, and SQL
  • Tune Spark jobs to improve performance
  • Work closely with product managers, designers, and engineers in order to collect the right data that will help them better understand our customers, product usage, or our own operations
  • Work with Data Analysts to build the right analytics reports
  • Have a meaningful impact on many teams at Datadog thanks to data
  • Join a tightly knit team solving hard problems the right way
  • Grow with the company


  • You are fluent in several programming languages such as Python, R, or Scala
  • You have 2+ years of work experience in building ETL pipelines in production
  • You value code simplicity and performance
  • You have work experience with data storage such as AWS S3, Redshift or similar.
  • Being a SQL expert is a minimum for this position
  • You are fluent with command line
  • You enjoy wrangling huge amounts of data and exploring new data sets
  • You have a natural curiosity and investigative mindset - driven to know “why”.
  • You can explain complex datasets in very clear ways
  • You want to work in a fast, high-growth startup environment and thrive on autonomy


Bonus points:

  • You are familiar with Spark and/or Hadoop
  • Experience with AWS Redshift and S3

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