Senior Backend Engineer, Home Surfaces

Spotify•Boston, MA

1d•Remote

About The Position

The Personalization team at Spotify focuses on enhancing the listener experience by making decisions about what to play next more enjoyable. The Home Podcasts Squad specifically develops systems for podcast recommendations across key Spotify surfaces like Home, the Podcast Subfeed, and the Now Playing view. This involves creating ranking systems and features such as topic-based shelves and cross-content recommendations to aid users in discovering podcasts. The role of a Senior Backend Engineer is to build and advance the backend infrastructure and pipelines that power these personalized podcast recommendation experiences for millions of users globally. This includes working on systems for identifying, retrieving, ranking, and filtering relevant podcast content.

Requirements

Experience building production systems with Java.
Experience designing distributed, high-volume services and deploying, operating, and evolving them in production.
Experience working directly with stakeholders to understand requirements and design APIs and systems for broad adoption.
Strong understanding of system design, data structures, and algorithms.
Interest in large-scale data processing technologies and their application to personalized product experiences.
Comfort working in an environment that encourages experimentation, learning, and rapid iteration.
Ability to use data to inform technical and product decisions and a focus on understanding the impact of built systems.
Experience with technologies such as gRPC, GCP, BigQuery, Bigtable, or similar tools and platforms.

Responsibilities

Architect, build, and evolve backend systems that support personalization and recommendations at Spotify scale.
Design reliable, scalable, and performant services capable of supporting high-volume recommendation workloads.
Build and improve the infrastructure and pipelines that enable efficient retrieval, ranking, and delivery of personalized podcast recommendations.
Partner closely with Product Managers, Engineers, Data Scientists, and Designers to develop new recommendation experiences and define experimentation strategies.
Take ownership of backend systems throughout their full lifecycle, including technical design, implementation, deployment, monitoring, and continuous improvement.
Utilize experimentation and data to understand the impact of system changes on the listener experience and inform future development.
Navigate ambiguous technical problems, make informed engineering trade-offs, and contribute to the long-term architecture of personalization systems.
Share knowledge and engineering practices with teammates to foster the development of reliable systems and team growth.