spotify - Staff Data Engineer — Subscriptions User Understanding
Requirements
• You enjoy solving broad, cross-cutting engineering challenges and bringing teams together around a shared technical vision. • You have extensive experience designing, building, and operating large-scale cloud-native data platforms. • You have deep experience building reliable distributed data pipelines using technologies such as Scio, BigQuery, Dataflow, GCS, SQL, Python, or similar cloud-native tools. • You have a strong understanding of modern data modeling, metadata management, governance, and data quality practices. • You know how to balance immediate business needs with long-term architectural sustainability. • You influence technical direction through strong communication, sound judgment, and collaboration rather than formal authority alone. • You communicate effectively with engineers, product managers, data scientists, analysts, and senior leadership. • You enjoy mentoring engineers and helping technical teams grow through coaching, technical guidance, and thoughtful feedback. • ## Where You'll Be • We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location (excluding France due to on-call restrictions). • This team operates within the Central European and GMT time zone for collaboration. • 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
• Define and drive the long-term data engineering strategy for the Subscriptions User Understanding domain, identifying opportunities that improve scalability, reliability, and business impact. • Partner with Product, Engineering, Data Science, Analytics, and Platform teams to turn complex business challenges into durable, well-designed data solutions. • Lead architectural decisions and establish engineering best practices for data quality, governance, observability, reliability, and operational excellence across multiple squads. • Design data models and platform architecture that support sustainable growth toward one billion users while balancing performance, cost, and maintainability. • Simplify complex systems, reduce technical debt, and improve the developer experience across the broader data ecosystem. • Mentor senior engineers, influence technical direction through collaboration, and help foster a culture of thoughtful engineering, knowledge sharing, and continuous improvement.
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