Senior Backend Data Engineer

Senior Backend Data Engineer

Spotify

Stockholm or London

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

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