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Data Engineer – Content Intelligence 395 views

Delivering the best Spotify experience possible. To as many people as possible. In as many moments as possible. That’s what the Experience team is all about. They use a deep understanding of consumer expectations to enrich the lives of millions of their users all over the world, bringing the music and audio they love to the devices, apps and platforms they use every day.

Have you ever had a debate at a party about who originally wrote a song versus who covered it? Tried to find a sample you loved more than the song you heard it in? Wondered who was actually in the recording booth for your favorite song (on both sides of the glass)? Wonder what Britney Spears, Nsync, Pink, Katy Perry, Taylor Swift, and The Weeknd all have in common? (The same songwriter wrote Billboard number-one singles for all of them). Who gets paid every time we sing “Happy Birthday”?

Music attribution at scale is one of the great unsolved technical problems of the music industry, and Spotify is building powerful technology to solve it. Their goal is to solve this problem for the tens of millions of music tracks playable on Spotify, building a knowledge graph through innovative machine learning models, deep domain expertise, and close integration with human-in-the-loop processes across Spotify and the industry. Content Platform’s catalog data powers Spotify experiences from Artist pages in the app, search and recommendations, human playlist curation, Spotify for Artists, and their music industry-facing strategy.

Their teams are composed of product, machine learning, data and backend engineers, and subject matter experts who average 11 years behind the scenes in the music industry.

Come join the team of talented engineers who share a common interest in distributed systems, scalability, and continued development. You will build the data pipelines that power Spotify’s  application, scale highly distributed systems, and continuously improve their engineering practices. Above all, your work will impact the way the world experiences music.

What You’ll Do:

  • Build large-scale batch and real-time data pipelines with data processing frameworks like Scio, Beam, Spark, and Flink, deployed and scaled via Google Cloud Platform.
  • Construct architectures to synthesize signals from disparate sources (including catalog metadata, audio vectors, and human-generated annotations) and populate scalable data solutions delivering insights about the music industry to Spotify product teams.
  • Use standard methodologies in continuous integration and delivery.
  • Help drive optimization, testing, and tooling to improve data quality.
  • Collaborate with other product managers, software engineers, ML experts, and stakeholders, taking learning and leadership opportunities that will arise every single day.
  • Work in multi-functional agile teams to continuously experiment, iterate and deliver on new product objectives.

Who You Are:

  • You have professional experience working in a product-driven environment.
  • You know how to work with high-volume heterogeneous data, preferably with distributed systems and data stores such as Hadoop, Spark, HBase, Cassandra.
  • Experience with graph databases (such as Neo4j), graph algorithms, and/or ontological modeling is a plus.
  • Writes distributed, high-volume services in Java or Scala.
  • Deep understanding of system design, data structures, and algorithms.
  • Knowledgeable about data modeling, data access, and data storage techniques and are able to demonstrate these skills to make architectural decisions based on product opportunities.
  • You care about agile software processes and iterative delivery, data-driven development, reliability, and responsible experimentation.
  • You understand the value of collaboration within teams.

Spotify transformed music listening forever when they launched in 2008. Their mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything they do is driven by their love for music and podcasting. Today, they are the world’s most popular audio streaming subscription service.

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