Data Engineer - Content Intelligence

New York City

Applications have closed

Spotify

We grow and develop and make wonderful things happen together every day. It doesn't matter who you are, where you come from, what you look like, or what music you love. Join the band!

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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. We use our deep understanding of consumer expectations to enrich the lives of millions of our users all over the world, bringing the music and audio they love to the devices, apps and platforms they use every day. Know what our users want? Join us and help Spotify give it to them. 
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 we’re building powerful technology to solve it. Our 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 our music industry-facing strategy.
Our 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 our team of talented engineers who share a common interest in distributed systems, scalability, and continued development. You will build the data pipelines that power our application, scale highly distributed systems, and continuously improve our 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.

Where You'll Be:

  • We are a distributed workforce enabling our band members to find a work mode that is best for them.
  • Where in the world? For this role, you will be working US East Coast hours.
  • Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.
Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
Spotify transformed music listening forever when we launched in 2008. Our 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 we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.
Global COVID and Vaccination DisclosureSpotify is committed to safety and well-being of our employees, vendors and clients. We are following regional guidelines mandating vaccination and testing requirements, including those requiring vaccinations and testing for in-person roles and event attendance. For the US, we have mandated that all employees and contractors be fully vaccinated in order to work in our offices and externally with any third-parties. For all other locations, we strongly encourage our employees to get vaccinated and also follow local COVID and safety protocols.

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Agile Architecture Cassandra Data pipelines Data quality Distributed Systems Engineering Flink GCP Google Cloud Hadoop HBase Machine Learning ML models Neo4j Pipelines Scala Spark Streaming Testing

Perks/benefits: Career development Equity Team events

Region: North America
Country: United States
Job stats:  8  1  0
Category: Engineering Jobs

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