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Data Engineer

Spotify is looking for experienced data engineers to join us in NYC on our mission to create the world's best music player. As a Data Engineer, your job is to work with huge data sets and analyze data using algorithms and machine learning. You will help us improve music recommendations, build top lists, forecast ad delivery, identify trends, and much more.

We work on large scale systems processing terabytes of data every day, using a wide range of tools. The data infrastructure is an integral part of Spotify's backend architecture and it powers most of the user facing features. Some challenging tasks include scaling music recommendations up to millions of users, or how to push out thousands of updates per second to users in real time.

As a data infrastructure engineer at Spotify, you will help us design, build, scale and evolve these systems and their next generation. We are looking for brave candidates who share our passion for tackling infrastructural complexity and building platforms that can seamlessly scale through multiple orders of magnitude.  

 

Responsibilities

  • Design, build, scale, and evolve our current large scale systems and their next generation
  • Work with huge data sets and work with Machine Learning engineers on analyzing this data using algorithms and machine learning 
  • Hack on Spotify backend software components
  • Assume ownership over certain components and continuously work to improve them
  • Run A/B tests to determine what makes our users the happiest
  • Be proactive and constantly pay attention to the scalability, performance and availability of our systems
  • Take an active interest in our features and our user happiness
  • Occasionally help out with recruitment


Requirements 

  • BS in Computer Science or similar
  • Strong and proven development skills, preferably in Python/Java
  • Strong algorithms and data structures background
  • Experience working in a Linux environment or similar
  • Has worked with web-scale data sets, preferably in Hadoop
  • Experience with Cassandra, Kafka, Pig, Hive, Storm and other tools are a great plus
  • Experience with machine learning or related fields is another great plus