Data Engineer II
Description
The Platform team creates the technology that enables Spotify to learn quickly and scale easily, enabling rapid growth in our users and our business around the globe. Spanning many disciplines, we work to make the business work; creating the infrastructure, tooling, frameworks, and capabilities needed to welcome a billion customers.
Bard is a critical squad within Spotify’s Financial Engineering (FinE) Solutions area. We build and maintain the systems that ensure accurate, timely royalties and financial reporting for Audiobook and Lyrics licensors — supporting some of Spotify’s most strategically important creator-focused products. We’re a cross-functional, collaborative team of backend and data engineers working closely with Finance and the Audiobooks mission to deliver trustworthy, scalable systems.
What You'll Do
Design, build, and evolve scalable data pipelines and systems that ensure financial accuracy and integrity at scale. Explore and apply Spotify’s Data and AI ecosystem to solve engineering problems and improve developer efficiency. Partner closely with Finance and Audiobooks stakeholders to understand their needs and deliver financially impactful features. Deep-dive into the Audiobooks royalties domain and support feature development across reporting and payout workflows. Contribute to design discussions, architectural decisions, code reviews, and team-wide engineering practices. Lead the delivery of small projects or workstreams within your first months on the team. Continuously evaluate and improve the team’s tools, quality standards, and ways of working.
Who You Are
You know how to work with large-scale data ecosystems and are comfortable with SQL and distributed processing tools (e.g., Spark, Beam, Scio, or similar). You are experienced with JVM-based or similar languages (e.g., Scala, Java, or other production-grade languages), and you learn new technologies quickly. You have a deep understanding of data modeling, pipeline design, and how to build reliable systems in a fast-moving environment. You care about using AI as a practical tool — from prompting to agentic workflows — to support engineering decision-making and accelerate delivery. You enjoy collaborating closely with partners, guiding them through end-to-end solutions and ensuring clarity and shared understanding. You have experience contributing to testing and quality practices using frameworks such as Cucumber or comparable tooling. You care about continuously improving how the team works in a constructive way, calling to action and taking the lead on proposed ideas.
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.