Backend Engineer - Music

The Music Mission team owns Spotify's end to end proposition for music creators and the experiences they create for fans. The organization is dedicated to building tools and services to enable creation, promotion, expression, and monetization at scale. Our team makes music videos easy for fans to discover and meaningful for artists, powered by scalable, intelligent infrastructure that grows with our catalog. We're building personalized music video playlists, sorting videos into meaningful categories, and learning which videos listeners are most likely to love, then helping that content reach the right people. As a Backend Engineer, you'll help shape how millions of listeners experience music videos on Spotify, working alongside Data Engineers, Backend Engineers, and partners across product and design.

Build and run production backend systems that improve how listeners discover and enjoy music videos. Design, develop, and evolve scalable backend services and APIs that support high-traffic parts of the Spotify app. Develop and maintain Java services and Scio data pipelines used by millions of listeners every day. Partner with product managers and engineers to solve complex problems and create smooth, enjoyable experiences for listeners. Contribute to system design, code quality, and reliable, well-run systems as part of an autonomous, cross-functional squad. Explore and experiment with AI tools available at Spotify to improve how we build and ship.

You have experience with Java or another JVM language, and familiarity with (or interest in learning) data pipeline tools like Scio, Apache Beam, or similar. You've built and operated distributed, high-volume services in production, ideally on a cloud platform such as Google Cloud Platform. You're comfortable with system design, data structures, and algorithms, and use data to inform how you design systems and make decisions. You work directly with partners to understand their needs and turn them into scalable backend systems, APIs, and pipelines. You enjoy working in teams where experimentation and iteration are part of everyday work. You care about code quality, reliability, and maintainability, and take pride in shipping well-crafted work. You bring a collaborative mindset and are comfortable working across team boundaries. Experience in data engineering or machine learning is a bonus, not a requirement.

We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home. This team operates within the US Eastern timezone for collaboration

laptop-ats-crawler v3