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Data Engineer for Personalization Systems
7 hours ago
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Data Engineer, Personalization, StockholmOur team at TN Sweden makes deciding what to play next on Spotify easier and more enjoyable for every listener.
We are at the forefront of development for Spotify's recommendation systems, which power personalized content across music, podcasts, and audiobooks. As a data engineer with backend experience, you will join our team and help develop and shape the way Spotify recommendations work.
You'll be able to grow your skills in engineering at scale, drive business impact, and join a high-energy team environment.
Key Responsibilities
- 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
- Deliver scalable, testable, maintainable, and high-quality code
- Share knowledge, promote standard methodologies, making the team better through mentorship and constructive accountability.
Required Skills and 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 practices
- You 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
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