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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.
What You Will Do
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
Who You Are
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
Where You’ll Be
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.
Skills Required
- 5+ years of relevant engineering experience
- Strong experience in backend and/or data engineering
- Deep expertise in backend or data engineering and ability to work across both disciplines
- Experience building and scaling large-scale distributed systems
- Strong programming experience in Java, Scala, and/or Python
- Ability to design systems for scalability, reliability, performance, and cost efficiency
- Ability to take 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 across backend, data, ML infrastructure, and AI
- 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
- Exposure to large-scale multimedia processing, audio processing, search, or recommendation systems
Spotify Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Spotify and has not been reviewed or approved by Spotify.
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Flexible Benefits — Employees consistently praise the total compensation package beyond base salary, highlighting a mix of RSUs, cash incentives, and stipends alongside core pay. The package is described as flexible and customizable through equity choices (e.g., RSUs, options, cash) that can be tailored for long-term wealth building.
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Leave & Time Off Breadth — Time-off offerings are repeatedly highlighted as substantial, including generous vacation, paid sick days, volunteer time, and flexible holidays. These policies are framed as a meaningful part of the overall rewards experience beyond salary.
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Healthcare Strength — Health coverage is portrayed as comprehensive, spanning medical, dental, vision, life insurance, disability coverage, and mental health support. Additional employer contributions to HSAs are cited as strengthening the overall health and wellness value proposition.
Spotify Insights
What We Do
Spotify transformed music listening forever when it launched in Sweden in 2008. Discover, manage and share over 50m tracks for free, or upgrade to Spotify Premium to access exclusive features including offline mode, improved sound quality, and an ad-free music listening experience.
