The Personalization team makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music, podcasts and audiobooks better than anyone else so that we can make great recommendations to every individual and keep the world listening. Every day, hundreds of millions of people all over the world use the products we build which include destinations like Home and Search as well as original playlists such as Made For You, Discover Weekly and Daily Mix.
We are looking for a Data engineer with backend experience to join our team. We build the fundamental platform to ingest, model and materialize high-scale, event-driven user behavior data so Spotify can make personalized recommendations. Our platform tools support easy experimentation and productionisation. This is a unique opportunity to help develop and shape the way Spotify recommendations work. You’ll be able to grow your skills in engineering at scale, drive long term platform vision, and join a high-energy, positive team environment!
Join us and you’ll keep millions of users listening to great recommendations every day.
What You’ll Do
Work with large-scale data pipelines with data processing frameworks like Scio, BigQuery, Google Cloud Platform and Apache Beam.
Develop, deploy, and operate Java services that impact millions of users.
Work towards supporting machine learning projects powering the experience that suits each user individually.
Collaborate with other engineers, product managers and stakeholders, taking on learning and leadership opportunities that will arise every single day.
Deliver scalable, testable, maintainable, and high-quality code.
Share knowledge, promote standard methodologies, making your team the best version of itself through mentorship and constructive accountability.
Who You Are
You have experience building and operating large-scale backend systems and data pipelines in production environments, with a focus on reliability, scalability, and maintainability.
You are proficient in Java and have experience developing, deploying, and supporting services that serve large numbers of users.
You have hands-on experience working with modern data processing frameworks and cloud technologies such as Apache Beam, Scio, BigQuery, or similar large-scale data platforms.
You are comfortable working with data-intensive systems and are excited about building infrastructure and services that support machine learning and personalized user experiences.
You care deeply about software engineering best practices and strive to deliver high-quality, well-tested, and maintainable code.
You are curious about emerging technologies and excited by the opportunity to work at the intersection of large-scale data processing, backend engineering, and machine learning.
Where You’ll Be
This role is based in New York.
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.
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.
Spotify Insights
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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.
