On the Personalization Team, we seek to understand the world of music and podcasts better than anyone else so that we can make great recommendations to every individual person and keep the world listening. Everyday, 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 "Discover Weekly" and “Daily Mix.” We're a team of technologists, product insight experts, designers, and product managers in Boston, New York, Stockholm, and London.As a Backend Engineer with data engineering experience, you will closely collaborate with our internal customers to determine the best API and backend system design to meet their scalability needs. In this role, you’ll help craft our data strategy and build the systems that power smarter, more intuitive features across Spotify. You'll bring your expertise in building scalable, reliable backend services while also applying modern data engineering practices—such as data quality, monitoring, and reproducibility—to support ML-powered recommendations and user-facing experiences. Above all, your work will impact the way the world experiences music. What You'll Do

Architect, develop, and operate scalable and highly available distributed systems. Collaborate with internal stakeholders to design scalable backend systems and data pipelines that power ML-based music recommendations and personalized experiences. Partner with ML, Data, and Backend Engineers to improve the reliability, observability, and efficiency of our data and backend stack. Advocate for modern engineering practices—, data quality, monitoring, reproducibility—across the team and broader org. Contribute to strategic decisions around data architecture and technical direction. Work on what you want during regular hack days and bi-annual hack weeks. Who You Are

You have proven experience in backend and data engineering, including building scalable services, reliable data pipelines, and robust data platforms. You possess a strong understanding of data systems, distributed systems, and cloud-based infrastructure (, Google Cloud Platform), and are comfortable working with large datasets using tools such as SQL and BigQuery. You collaborate effectively with ML, Data, and Backend teams, and understand the challenges of supporting ML models in production environments. You take initiative to improve systems, mentor peers across disciplines, and drive technical decisions independently. You prioritize code quality, data observability, and monitoring, and have experience working directly with stakeholders to build scalable, reusable APIs and systems. You thrive in fast-paced environments that value experimentation, iteration, and continuous learning. Where You'll Be

We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have This team operates within the Eastern Standard time zone for collaboration. The United States base range for this position is $125,300 - $179,000 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays. This range encompasses multiple levels. Leveling is determined during the interview process. Placement in a level depends on relevant work history and interview performance. These ranges may be modified in the future.