Data Engineer – Internal Analytics Platform

Datadog
Datadog

Job Overview

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 companyRequirements:* 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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