The Role
Lead design and execution of scalable batch and streaming data platforms for subscription analytics and ML. Define long-term data strategy, drive architecture and best practices, reduce technical debt, mentor engineers, and partner cross-functionally to improve data quality, governance, observability, and platform reliability for subscriber growth.
Summary Generated by Built In
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, 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.
Who You Are
- 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.
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.
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.
Skills Required
- Extensive experience designing, building, and operating large-scale cloud-native data platforms
- Deep experience building reliable distributed data pipelines using Scio, BigQuery, Dataflow, GCS, SQL, and Python
- Strong understanding of modern data modeling, metadata management, governance, and data quality practices
- Proven ability to define long-term data engineering strategy and lead architectural decisions across teams
- Experience simplifying complex systems, reducing technical debt, and improving developer experience
- Demonstrated mentorship and ability to influence technical direction across senior engineers and stakeholders
- Effective communication with engineers, product managers, data scientists, analysts, and senior leadership
- Ability to work within the EMEA region and collaborate in Central European/GMT time zones (France excluded)
Spotify Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Spotify and has not been reviewed or approved by Spotify.
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Flexible Benefits — Employees consistently praise the total compensation package beyond base salary, highlighting a mix of RSUs, cash incentives, and stipends alongside core pay. The package is described as flexible and customizable through equity choices (e.g., RSUs, options, cash) that can be tailored for long-term wealth building.
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Leave & Time Off Breadth — Time-off offerings are repeatedly highlighted as substantial, including generous vacation, paid sick days, volunteer time, and flexible holidays. These policies are framed as a meaningful part of the overall rewards experience beyond salary.
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Healthcare Strength — Health coverage is portrayed as comprehensive, spanning medical, dental, vision, life insurance, disability coverage, and mental health support. Additional employer contributions to HSAs are cited as strengthening the overall health and wellness value proposition.
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The Company
What We Do
Spotify transformed music listening forever when it launched in Sweden in 2008. Discover, manage and share over 50m tracks for free, or upgrade to Spotify Premium to access exclusive features including offline mode, improved sound quality, and an ad-free music listening experience.
