Remote Staff Data Engineer Subscriptions User Understanding
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. Be one of the first applicants, read the complete overview of the role below, then send your application for consideration.
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 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 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.
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).
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. xehkeey If you would like more information about how your data is processed, please contact us. Find our AI notice here:
Remote working/work at home options are available for this role.
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 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 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.
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).
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. xehkeey If you would like more information about how your data is processed, please contact us. Find our AI notice here:
Remote working/work at home options are available for this role.