Data Engineer – Wrapped – Fixed Term Full Time

The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.

Wrapped is one of Spotify’s most iconic and beloved user experiences, a cultural moment that helps hundreds of millions of listeners reconnect with the soundtrack to their year. The Timeturners squad, part of Spotify’s Personalization Mission, powers the data behind Wrapped by building the datasets and systems that fuel personalized data stories for more than 300M users globally.

As a Data Engineer on Timeturners, you’ll collaborate with Data Scientists, engineers, music experts, and partner teams to transform listening behavior into meaningful, joyful, and highly personalized user experiences. From evaluating new data story concepts to scaling pipelines that power AI-driven playlist experiences, you’ll help shape how millions of fans experience Wrapped every year.

This is a fixed term contract role running from June through December 2026.

What You’ll Do

• Design, build, and maintain distributed data pipelines that power Spotify Wrapped data stories and personalized experiences for more than 300M users globally.
• Partner with Data Scientists to evaluate and operationalize new Wrapped story concepts, balancing personalization, scalability, and eligibility requirements.
• Build scalable systems that process large-scale listening data and generate insights that celebrate users’ unique listening journeys.
• Develop and optimize pipelines supporting AI-powered personalized playlist experiences and recommendation technologies.
• Collaborate with partner teams to integrate social and shared listening experiences into Wrapped and adjacent user experiences.
• Contribute to technical excellence by improving reliability, observability, performance, and development velocity across the squad’s data systems.
• Support experimentation and iteration on new storytelling concepts beginning early in the product development cycle.
• Work cross-functionally with engineering, product, design, and music domain experts to bring large-scale personalized experiences to life.

Who You Are

• Experience of working in a product-driven engineering environment.
• You have experience working with high-volume, heterogeneous datasets using distributed systems and big data technologies such as Python, Scala, Scio, Ray, Apache Spark, or similar frameworks.
• You are proficient in designing and building distributed data pipelines in Python, Scala, or Java, including experience with frameworks such as Scio and platforms like Dataflow.
• You understand data modeling, data access, and storage techniques across both batch and analytical processing systems.
• You have experience working with large-scale analytical systems such as BigQuery or similar technologies.
• You value iterative software development, data-driven decision making, reliability, responsible experimentation, and cost-efficient engineering practices.
• You thrive in collaborative environments and enjoy working closely with cross-functional teams across engineering, data science, and product.
• You are a creative problem solver who enjoys building products that create meaningful experiences for millions of users.
• You are excited by the challenge of turning research ideas and experimental concepts into reliable, scalable production systems.

Where You’ll Be

• We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.
• This role can be based within the United States (EST time zone) or within the EMEA region as long as we have a work location.
• This fixed term contract will run from June 2026 through December 2026.

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: https://lifeatspotify.com/ai-notice

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