At Spotify, we’re on a mission to unlock the potential of human creativity by connecting millions of artists with billions of fans around the world. The Search product area is central to that mission—reinventing how users find and connect with content in new and relevant ways.
We’re looking for a Data Engineer to join a squad passionate about delivering pioneering search experiences powered by Machine Learning (ML) and Large Language Models (LLMs). In this role, you’ll help craft the team’s data strategy and build the systems that power smarter, more intuitive discovery on Spotify.
You’ll work alongside a dedicated mix of ML and Backend Engineers to tackle some of Spotify’s most exciting challenges in retrieval, ranking, and personalization. If you're excited by data systems, ML-powered products, and the opportunity to impact how millions of people explore audio content—this is the role for you.
What You'll Do
- Design, build, and maintain scalable, reliable data pipelines that support advanced search capabilities.
- Partner closely with ML and Backend Engineers to enable features like organic search retrieval and personalized recommendations.
- Continuously assess and improve the health of the team’s data stack, driving efforts to increase reliability, observability, and efficiency.
- Advocate for modern data engineering practices—e.g., data quality, monitoring, reproducibility—across the squad and broader org.
- Contribute to technical direction and strategic decisions around how we handle and use data for ML.
Who You Are
- You have proven experience in data engineering, including creating reliable, efficient, and scalable data pipelines using data processing frameworks such as Scio, DataFlow, Beam or equivalent.
- You are comfortable working with large datasets using SQL and data analytics platforms such as BigQuery.
- You are knowledgeable in cloud-based environments, preferably with an understanding of Google Cloud Platform.
- You are familiar with A/B testing frameworks and experimentation platforms.
- You’re eager to collaborate with ML teams and understand the unique demands of supporting ML models in production.
- You bring a mentor attitude and enjoy helping peers (even from other subject areas) grow their data proficiency.
- You take initiative in improving data systems and practices, and can drive improvements independently when needed.
- You prioritize data quality, monitoring, and clarity, and understand their importance in reliable ML systems.
- You thrive in fast-paced, collaborative environments where learning and iteration are part of the culture.
- You’re passionate about search, discovery, and the challenge of helping users find the right content at the right time.
Where You'll Be
- We offer you the flexibility to work where you work best! For this role, you can be within Sweden, as long as we havea work location.
- This team operates within the CET 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.
Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.
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