Senior Backend Data Engineer – Content Intelligence

The Experience team at Spotify designs the consumer experience across various screens, platforms, and partner integrations. The Content Intelligence Product Area is a core part of Spotify's Content Platform, focusing on creating deep, machine-readable understanding of content. We're seeking a Senior Backend Data Engineer to help build and scale systems powering content understanding.

Responsibilities

• Design, build, and evolve scalable backend and data systems powering Spotify's 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 your 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 closely with other Engineers to plan and deliver technical solutions
• Contribute to AI and LLM-enabled workflows and infrastructure, including systems 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

Requirements

• 5+ years of relevant engineering experience, with strong experience in backend and/or data engineering
• Deep expertise in either 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
• Understanding of designing systems with scalability, reliability, performance, and cost in mind
• Comfortable 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
• Comfortable operating in an environment where backend, data, ML infrastructure, and AI increasingly overlap
• Ability to participate in a shared on-call rotation
• Experience with ML infrastructure, AI/LLM systems, agents, model evaluation, or integrating model APIs at scale is a plus
• Exposure to large-scale multimedia processing, audio processing, search, or recommendation systems is a plus