Spotify: Data Engineer

Spotify is looking for a Data Engineer to join us in our Personalization organisation. The Personalization teams mission is to match listeners, music and audio in a personal and meaningful way to create great listening experiences. We are constantly working together using state of the art machine learning and applied research to create the best personalized soundtracks that connect people to music and audio.

You will clean and connect logs across a broad range of services - interaction logs, user behaviors, contextual streaming data, etc. to enable the creation of training data and analytics around the performance of our machine learning recommender systems. You will create and monitor pipelines generating metrics and useful datasets that power internal dashboards, providing insights into the Personalization mission.

You will build data driven solutions to bring music and digital media experiences to hundreds of millions of active users and millions of creators by matching fans with creators in a personal and relevant way. Above all, your work will impact the way the world experiences art.

What youll do:

  • Work with state-of-the-art data processing frameworks, technologies, and platforms
  • Design, build and maintain data pipelines and ad-hoc solutions to gather relevant data across the sprawling data infrastructure of Spotify
  • Work from our office in New York or Boston (USA)
  • Improve data quality through testing, tooling and continuously evaluating performance

Who you are:

  • You know the Scala and Python languages
  • You have experience in developing/building data pipelines (batch or streaming)
  • You are interested in being the glue between engineering and analysis, and have an eye for data accuracy and integrity
  • You have experience with one or more higher-level JVM-based data processing frameworks such as Beam, Dataflow, Crunch, Scalding, Storm, Spark, or something we didnt list- but not just Pig/Hive/BigQuery/other SQL-like abstractions
  • You are knowledgeable about data modeling, data access, and data storage techniques
  • Tools and infrastructure such as GCP (google cloud platform) is a plus

We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply and we encourage everyone to come be a part of changing the way the world listens to music.

Full-time