Remote Staff Data Engineer Subscriptions User Understanding
8 days ago
Redhill
2026-10-06T00:00:00 Redhill Surrey GB RH1 1 Any 2027-01-04T19:01:08.917 Spotify is on an ambitious path to reach one billion users and 100 billion in revenue, and the Subscriptions User Understanding team plays a key role in making that possible. Our team builds the foundational data platform that helps Spotify understand conversion, retention, engagement, and subscriber health for more than 200 million Premium subscribers around the world. We enable better decisions across analytics, experimentation, machine learning, and product development. We’re looking for a Staff Data Engineer who combines deep technical expertise with strategic thinking. You'll help define the long-term direction of our data ecosystem, influence engineering across multiple teams, and build the foundations that will scale with Spotify's future. • Define and drive the long-term data engineering strategy for the Subscriptions User Understanding domain, identifying opportunities that improve scalability, reliability, and business impact., • Design scalable batch and streaming data platforms that power analytics, experimentation, machine learning, and subscriber experiences., • 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., • 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., • You are motivated by building platforms that directly influence Spotify's long-term subscriber growth and business success. 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. 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. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: #s1-Gen Spotify is on an ambitious path to reach one billion users and 100 billion in revenue, and the Subscriptions User Understanding team plays a key role in making that possible. Our team builds the foundational data platform that helps Spotify understand conversion, retention, engagement, and subscriber health for more than 200 million Premium subscribers around the world. We enable better decisions across analytics, experimentation, machine learning, and product development. We’re looking for a Staff Data Engineer who combines deep technical expertise with strategic thinking. You'll help define the long-term direction of our data ecosystem, influence engineering across multiple teams, and build the foundations that will scale with Spotify's future. What You’ll Do Define and drive the long-term data engineering strategy for the Subscriptions User Understanding domain, identifying opportunities that improve scalability, reliability, and business impact. Design scalable batch and streaming data platforms that power analytics, experimentation, machine learning, and subscriber experiences. 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 #J-18808-Ljbffr
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