3D data processing, Apache Airflow, Apache Beam, Apache Flink, Data Engineering, DevOps, Docker, Google BigQuery, Google Cloud Platform (GCP), Java Programming, JVM, Machine learning techniques, Scala Programming, SPARK Programming
The Personalization team makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music and podcasts better than anyone else so that we can make great recommendations to every individual and keep the world listening. Every day, hundreds of millions of people all over the world use the products we build which include destinations like Home and Search as well as original playlists such as Made For You, Discover Weekly and Daily Mix.
We are looking for a Data engineer with backend experience to join our team. We are at the forefront of development for Spotify’s recommendation systems, which power personalized content across music, podcasts, and audiobooks. This is a unique opportunity to help develop and shape the way Spotify recommendations work. You’ll be able to grow your skills in engineering at scale, drive a ton of business impact, and join a high-energy, positive team environment!
Join us and you’ll keep millions of users listening to great recommendations every day.
What You'll Do
Who You Are
Where You'll Be
The United States base range for this position is $122,716 $175,308 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.
Spotify is a popular digital music streaming platform that was launched in 2008. It provides users with access to a vast library of music from various genres and artists around the world. Initially, Spotify started as a desktop application but has since expanded to include mobile and web-based versions as well. Key features of Spotify include: Music Catalog, Personalized Recommendations, Social Integration, Podcasts and Audio Content and Offline
London, UK
0-2 year