Spotify - Data Engineer – Platform
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Requirements
• 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 • Where You'll Be • 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. • The Canada base range for this position is $103,321 – $147,602 CAD plus equity. Benefits available for this position include extended health and dental coverage, retirement savings plans, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, and other benefits in accordance with Canadian employment standards. These ranges and benefits may be modified in the future. • 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.
Responsibilities
• 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
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