The Personalization (PZN) team at Spotify aims to enhance the listening experience by providing tailored recommendations for music, podcasts, and audiobooks.
The team is seeking a Backend Engineer with data experience to help build a platform that ingests, models, and serves high-scale user behavior data for personalized recommendations.
The role involves working with large-scale data pipelines using frameworks like Scio, BigQuery, Google Cloud Platform, and Apache Beam.
Responsibilities include developing, deploying, and operating Java services that impact millions of users, supporting machine learning projects, and collaborating with engineers, product managers, and stakeholders.
The engineer will deliver scalable, testable, maintainable, and high-quality code while promoting best practices through mentorship and accountability.
This position offers the opportunity to grow engineering skills at scale and contribute to the long-term vision of the platform in a positive team environment.
Requirements:
Candidates should be familiar with data modeling, data access, and data storage techniques.
Experience with distributed data processing frameworks such as Beam or Spark is required.
A desire to work in a team that employs agile software development processes, data-driven development, and responsible experimentation is essential.
Candidates should value collaborative work opportunities.
Benefits:
The United States base salary range for this position is $125,561 to $179,374, plus equity.
Benefits include health insurance, six months of paid parental leave, a 401(k) retirement plan, a monthly meal allowance, 23 paid days off, and 13 paid flexible holidays.
Spotify is committed to inclusivity and offers reasonable accommodations during the recruitment process to ensure accessibility for all candidates.
