Data Engineer, Personalization

The Personalization team at Spotify is seeking a Data Engineer with backend experience to join their team. This role is at the forefront of developing Spotify's recommendation systems, powering personalized content across music, podcasts, and audiobooks. The position offers a unique opportunity to shape how Spotify recommendations work, allowing you to grow your skills in engineering at scale, drive significant business impact, and join a high-energy, positive team environment.

Key responsibilities include:

• Building large-scale data pipelines using frameworks like Scio, BigQuery, Google Cloud Platform, and Apache Beam
• Developing, deploying, and operating Java services that impact millions of users
• Working on machine learning projects to power personalized user experiences
• Collaborating with engineers, product managers, and stakeholders
• Delivering scalable, testable, maintainable, and high-quality code
• Sharing knowledge and promoting standard methodologies

The ideal candidate should have:

• Strong knowledge of Scala and interest in sharing this knowledge
• Experience with JVM-based data processing frameworks (e.g., Beam, Dataflow, Spark)
• Experience deploying and operating Kubernetes-based Java applications
• Knowledge of DevOps best practices and familiarity with Docker
• Understanding of machine learning principles
• Commitment to high-quality code and agile software processes
• Value for collaboration and partnership within teams

This role offers the opportunity to keep millions of users engaged with great recommendations every day, making a significant impact on the Spotify user experience.