Spotify
Data Engineer, Personalization
. Full-time, Remote, US
$156k-$195k/year

About:

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.

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Job Description

- Build large-scale data pipelines with data processing frameworks like Scio, BigQuery, Google Cloud Platform and Apache Beam - Develop, deploy, and operate Java services that impact millions of users - Work on machine learning projects powering the experience that suits each user individually - Collaborate with other engineers, product managers and stakeholders, taking on learning and leadership opportunities that will arise every single day - Deliver scalable, testable, maintainable, and high-quality code - Share knowledge, promote standard methodologies, making your team the best version of itself through mentorship and constructive accountability.

Qualifications

- You know Scala well and are interested in spreading this knowledge in the team - You have experience with one or more higher-level JVM-based data processing frameworks such as Beam, Dataflow, Crunch, Scalding, Storm, Spark, Flink etc - You are experienced in deploying and operating Kubernetes based Java applications along with strong knowledge of DevOps best practicesYou have worked with Docker as well as Flyte, Luigi, Airflow, or similar tools - You have familiarity and knowledge of machine learning principles - You understand quality and you know what it means to ship high quality code - You care about agile software processes, data-driven development, reliability, and responsible experimentation - You understand the value of collaboration and partnership within teams

We bring 🍀 to our team

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