Senior Data Engineer - Financial Data Platform

Financial Engineering builds the platforms and tools that power Finance and enable strategic decisions across Spotify. Within this group, the Financial Data Platform team turns messy, fragmented realities into clean, reusable foundations. We partner closely with Finance, Product, and Data teams to shape the financial datasets and abstractions that unlock clarity, trust, and scale across the company. We build core datasets that represent key financial domains like Premium, Ads, and Royalties. We create libraries and tools that empower others to produce and trust financial data at scale.

What You'll Do:
Build core financial datasets and abstractions that serve as sources of truth for business-critical decisions. Design, prototype, and operate scalable data pipelines that process billions of records reliably. Apply product thinking to the full data lifecycle - from sourcing to documentation to exposure,  with a strong focus on meeting consumer needs. Define models and abstractions that simplify complex domains such as Premium, Ads, and Royalties. Drive strong engineering and data quality standards that improve trust, reusability, and maintainability. Collaborate with engineers, data scientists, finance partners, and business stakeholders to design intuitive data products. Contribute to tools and libraries that help other teams build high-quality financial data products at scale. Engage in mentorship and feedback practices that build accountability, inclusion, and growth across the team.

Who You Are:
You are comfortable working with Python, Java, or Scala and use them to build reliable, maintainable data pipelines. You know how to work with higher-level JVM-based processing frameworks such as Flink, Beam, Dataflow, or Spark. You are comfortable navigating ambiguity and moving forward when problem spaces are loosely defined. You are experienced in large-scale cloud-based data processing, ideally in Google Cloud Platform. You have strong analytical skills and communicate insights clearly across technical and non-technical audiences. You care about thoughtful data modeling and treat data as a long-lived product. You have a passion for clean, maintainable code and robust pipeline design. You are curious about systems and data, and you continually look for opportunities to improve them. You are skilled in SQL and familiar with large-scale platforms such as BigQuery. You value collaboration and build positive relationships across technical and business domains.

Where You'll Be:
This role is based in London. 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.

Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.

At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.

Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.