
Data Engineer for Recommendation Systems
9 hours ago
At Spotify, we're on a mission to help millions of users discover new music and podcasts. We're looking for a talented Data Engineer to join our Personalization team and contribute to the development of our recommendation systems.
Our GoalWe aim to create personalized experiences for every individual, making it easier for them to find their next favorite song or podcast. To achieve this, we need a robust data pipeline that can process large amounts of information efficiently.
Key Responsibilities- Design and implement large-scale data pipelines using frameworks like Scio, BigQuery, and Apache Beam.
- Develop and deploy Java services that impact millions of users, ensuring high-quality code and scalability.
- Collaborate with engineers, product managers, and stakeholders to drive business impact and growth.
- Work on machine learning projects that power personalized content across music, podcasts, and audiobooks.
- Experience with Scala and JVM-based data processing frameworks like Beam, Dataflow, Crunch, Scalding, Storm, Spark, Flink.
- Strong knowledge of DevOps best practices, including Docker and Kubernetes.
- Familiarity with machine learning principles and quality engineering.
- Able to work in an agile software environment and collaborate effectively within teams.
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