Data Infrastructure Engineer – Platform

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.

The Data Infrastructure product area sits at the heart of Spotify’s Platform mission, enabling teams across the company to solve complex data challenges at scale. We build the infrastructure and tooling that powers data pipelines used in some of Spotify’s most loved experiences, like Discover Weekly and Wrapped. As part of this team, you’ll collaborate with engineers across multiple squads to shape the future of data processing and developer experience at Spotify, especially as AI and intelligent agents become more central to how we work with data.

Build large-scale batch and real-time data processing tools on Google Cloud Platform, improving developer experience and standardizing workflows

Collaborate with product owners, engineers, and cross-functional squads to deliver impactful features across the data ecosystem

Expand and evolve Spotify’s data processing platform to meet growing and changing business needs

Improve the experience for data practitioners by driving best practices, tooling, and standardization across the ecosystem

Contribute to the evolution of a unified data platform, including efforts toward a data monorepo

Support the development of systems that enable AI agents to effectively interact with and leverage data infrastructure

You have 3+ years of experience working in data engineering or a related field

You are experienced with building and maintaining data pipelines using modern programming languages

You have a strong understanding of systems design, data structures, and scalable architectures

You are comfortable working with high-volume, heterogeneous datasets in distributed cloud environments

You have experience with Python or JVM-based data processing frameworks such as Spark, Flink, or Dataflow

You care deeply about developer experience and enjoy building tools that help others move faster

You apply solid engineering practices like continuous delivery, testing, and writing maintainable, high-quality code

You are curious about emerging technologies, including AI and agent-based systems, and how they can improve data workflows

This role is based in Toronto.

We offer you the flexibility to work where you work best! There will be some in-person collaboration, and we expect you to be within a commutable distance to the office.