Staff Data Engineer – Subscriptions User Understanding

🔥 6 minutes ago

🇬🇧 United Kingdom – Remote

⏰ Full Time

🔴 Lead

🚰 Data Engineer

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Spotify

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2008

📱 Media

👥 B2C

🛍️ eCommerce

Media • B2C • eCommerce

Spotify is a global audio streaming service company that offers its users access to a vast library of music and podcasts. Known for its focus on delivering personalized listening experiences, Spotify employs data scientists, engineers, and client partners across various global locations to continuously innovate and enhance its offerings. The company fosters a strong culture of diversity, equity, and impact, emphasizing belonging and inclusion in its workforce. Spotify is not only committed to shaping the future of audio entertainment but also to making a positive societal impact, with initiatives focused on social and environmental issues.

📋 Description

• 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.

🎯 Requirements

• Extensive experience designing, building, and operating large-scale cloud-native data platforms. • Deep experience building reliable distributed data pipelines using technologies such as Scio, BigQuery, Dataflow, GCS, SQL, Python, or similar cloud-native tools. • Strong understanding of modern data modeling, metadata management, governance, and data quality practices. • Ability to balance immediate business needs with long-term architectural sustainability. • Effective communication with engineers, product managers, data scientists, analysts, and senior leadership. • Enjoy mentoring engineers and helping technical teams grow through coaching, technical guidance, and thoughtful feedback.

🏖️ Benefits

• Flexible work arrangements