data engineer for content intelligence

Spotify is the world’s most popular audio streaming subscription service. The Experience team designs Spotify’s consumer experience across screens, platforms, and partner integrations. The Content Intelligence Product Area builds systems that create machine-readable understanding of audio, video, text, and images, enabling automation, safety, and new product experiences.

• Design, build, and evolve scalable backend and data systems powering content intelligence capabilities;
• Take end-to-end ownership of significant engineering projects, from technical design and architecture through implementation and operation;
• Build reliable infrastructure for large-scale content processing across audio, video, text, and images;
• Create RFCs and contribute to architectural decisions within the squad and across connected systems;
• Develop reliable and cost-efficient systems for high-throughput data and content-processing workloads;
• Work with distributed data systems and large-scale content-management infrastructure;
• Partner with other Engineers to plan and deliver technical solutions;
• Contribute to AI and LLM-enabled workflows and infrastructure for content understanding, enrichment, and processing;
• Evaluate and integrate AI capabilities into production systems at scale;
• Build a strong understanding of adjacent systems and contribute to a shared on-call rotation;
• Contribute to technical quality and engineering best practices across the team.

• 5+ Years of relevant engineering experience, with strong backend and/or data engineering experience;
• Deep expertise in backend or data engineering and comfort working across both disciplines;
• Experience building and scaling large-scale distributed systems;
• Strong programming experience in Java, Scala, and/or Python;
• Ability to design systems with scalability, reliability, performance, and cost in mind;
• Comfort taking end-to-end ownership of complex engineering problems;
• Ability to translate technical problems into designs, RFCs, and executable engineering plans;
• Effective communication and collaboration with engineering, product, and technical stakeholders;
• Comfort working in an environment where backend, data, ML infrastructure, and AI increasingly overlap;
• Ability to participate in a shared on-call rotation;
• Nice to have: experience with ML infrastructure, AI/LLM systems, agents, model evaluation, or integrating model APIs at scale; exposure to large-scale multimedia processing, audio processing, search, or recommendation systems.

• The role is based in London or Stockholm;
• Some in-person meetings, with flexibility to work from home.