Backend Engineer - Personalization - Tunesday

# Backend Engineer - Personalization - TunesdaySpotifyFull TimemidBoston, Massachusetts, USPosted Yesterday## Role OverviewSpotify is hiring a mid-level Backend Engineer - Personalization - Tunesday. This is a full-time role in Boston. Part of Spotify's Backend hiring, posted yesterday. Full responsibilities, required qualifications, and the apply link are listed in the description below.## Salary ContextSalary is not disclosed in this posting. Market median for Mid-level Backend roles is $115k-$166k (based on 71 comparable listings). Many employers share specifics during the interview process or after an initial screen.## Resume Keywords to IncludeMake sure these keywords appear in your resume to improve ATS scoringJavaScalaGCPKubernetesApacheElasticsearchBigQuerygRPCSign up free to auto-tailor your resume with all these keywords and get a higher ATS score## Job DescriptionThe 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.On the Tunesday squad, our mission is simple! When a user is looking for new music, we help them find the right content at the right time. Every week, hundreds of millions of people discover new artists and tracks through the experiences we build - Discover Weekly, Smart Shuffle, Playlist Extender, and This Is Artist. We are a team of backend & data engineers, data scientists & product experts but most of all, we are passionate about music!As a Backend Engineer on Tunesday, you will own and evolve the systems behind some of Spotify's most-loved playlist experiences. Your work will range from low-latency gRPC services handling real-time recommendation requests, to large-scale daily batch pipelines that process hundreds of millions of user signals to surface the right tracks. You will work closely with data scientists and product managers to bring new recommendation ideas to production and you will help define the engineering bar for how we build and evaluate those experiences.### What You'll Do* Design and operate services that serve personalized recommendations to users in real time, including Smart Shuffle and Discover Weekly* Build and maintain large-scale batch pipelines in Scala/Scio and Flyte that generate candidate pools, bloom filters, and personalization signals for hundreds of millions of users daily* Develop and maintain components within Spotify's Sessions Platform (SSP) that power playlist experiences end to end, from candidate retrieval to final serving* Collaborate with data scientists to operationalize research ideas, for example, expanding our definition of music discovery beyond simple listening recency, or integrating audio attributes like BPM and musical key into recommendation ranking* Be a technical leader in an autonomous, multi-functional team: drive architecture decisions, set engineering standards, and help the team ship faster with higher confidence### Who You Are* You have several years of experience as a Backend Engineer building and operating services at scale, with strong Java skills and comfort with gRPC and Protocol Buffers* You have hands-on experience with large-scale data pipelines, ideally Apache Beam/Scio or a similar batch processing framework (Spark, Flink) and with pipeline orchestration tools like Flyte or similar* You are comfortable working across the full backend stack: from online serving (Bigtable, Memcached, low-latency APIs) to offline data (BigQuery, Dataflow, dbt)* You bring curiosity about recommendation systems, search, or personalization, you want to understand not just how to build a system, but whether it is actually improving the user's music discovery experience* You care about quality and know what it means to ship reliable, observable, production-grade systems you think about SLOs, on-call burden, and correctness as part of your design* You thrive in an environment of experimentation and fast iteration; you use data to make decisions and are comfortable working with data scientists to evaluate the impact of changes* Experience with GCP (Kubernetes/GKE, Gantry, Dataflow, BigQuery, Bigtable) and Elasticsearch is a plusWhere You'll Be* We offer you the flexibility to work where you work best! For this role, you can be within the North Americas region as long as we have a work location.* This team operates within the Eastern time zone for collaboration.The United States base range for this position is $151,942 - $189,927 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays. This range encompasses multiple levels. Leveling is determined during the interview process. Placement in a level depends on relevant work history and interview performance. These ranges may be modified in the future.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.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: we are the world’s most popular audio streaming subscription service. #J-18808-Ljbffr