Senior Backend Data Engineer – Content Intelligence
Spotify · Stockholm ·
- Work mode
- Hybrid
- Seniority
- Senior
- Category
- Data engineering
- Experience
- 5+ years
Spotify · Stockholm ·
The Experience team designs Spotify’s consumer experience—end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints—from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.
The Content Intelligence Product Area is a core part of Spotify’s Content Platform within the Experience mission. We build systems that create deep, machine-readable understanding of content across audio, video, text, and images before it reaches users. This enables automation, safety, and entirely new product experiences. Our work powers content enrichment, quality analysis, annotation platforms, and scalable intelligence systems that allow teams across Spotify to build without needing direct content understanding expertise.
We’re looking for a Senior Backend Data Engineer to help build and scale the systems powering content understanding across Spotify. This role sits at the intersection of backend engineering, distributed data systems, ML infrastructure, and applied AI. You’ll take end-to-end ownership of significant engineering problems while working alongside other Engineers.
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
You have 5+ years of relevant engineering experience, with strong experience in backend and/or data engineering
You have deep expertise in either backend or data engineering and are comfortable working across both disciplines
You have experience building and scaling large-scale distributed systems
You have strong programming experience in Java, Scala, and/or Python
You understand how to design systems with scalability, reliability, performance, and cost in mind
You’re comfortable taking end-to-end ownership of complex engineering problems
You can translate technical problems into designs, RFCs, and executable engineering plans
You communicate effectively and enjoy collaborating with engineering, product, and technical stakeholders
You’re comfortable operating in an environment where backend, data, ML infrastructure, and AI increasingly overlap
You’re able 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
This role is based in London or Stockholm
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.