Every great song has a story behind it: a sample flipped into something new, a melody borrowed and reborn, a classic reinterpreted for a new generation. WhoSampled is where those stories live.
WhoSampled is the world's leading database of music samples, interpolations, cover songs, and remixes. Built over more than a decade by a passionate community of over 40,000 contributors, and verified by a dedicated team of moderators, it's become the definitive archive of music's creative lineage — visited by millions of fans each year. In late 2025, WhoSampled joined Spotify, powering SongDNA: a new experience that lets listeners explore the samples, covers, and interpolations woven into the music they love.
We're a small team with an outsized impact, and we're growing. As a Senior Fullstack Engineer, you'll be one of the first engineering hires into this team — a genuine opportunity to shape how WhoSampled evolves as a standalone product and as a foundational layer within Spotify's ecosystem.
As a small team, our work spans across the stack: you’ll work as much on data pipelines and backend APIs as you will on our web app. The ideal candidate is a generalist at heart — someone who's equally at home writing a Django view, tuning a PostgreSQL query, or shipping a UI improvement, and someone who gets results without waiting for someone else to own adjacent layers.
What You'll Do
- Build and maintain across the stack: Contribute to backend services, APIs, data pipelines, and where needed, frontend interfaces, embracing Spotify's infrastructure patterns and continuing making WhoSampled the industry-leader in showcasing the story behind the music.
- Improve metadata matching: Evolve how WhoSampled's database is matched to Spotify's catalog, moving beyond heuristics toward ML-assisted approaches, including entity resolution and LLM-powered disambiguation. Better matching means more of WhoSampled's archive surfaces meaningfully within Spotify.
- Drive infrastructure modernisation: Lead meaningful infrastructure work that brings WhoSampled onto more robust, scalable foundations, working closely with Spotify's platform and security stakeholders.
- Take end-to-end ownership: Design, build, ship, and operate. You're accountable for the reliability and performance of the systems you own, and proactive about improving them.
- Be AI-forward: Bring AI tooling into your engineering practice; whether for data quality, matching, operational automation, or developer productivity.
Who You Are
- Strong experience building production software, with depth in at least two of: backend services, frontend web, data systems, or infrastructure — and enough exposure to the others to move between them without stalling.
- You are comfortable moving between languages and stacks. You're strong in Python (ideally with Django experience) and Java. Our Django codebase is where the current product lives, and new services may go out in Java.
- You have production experience with Postgres — schema design, query tuning, and knowing when to reach for something else. Familiarity with ElasticSearch is a plus; you'll be tuning clusters with us, not from scratch.
- You have modern web app experience with TypeScript and React. You've shipped user-facing features, not just prototypes.
- You are comfortable with the production stack: Linux, GCP (or equivalent cloud), networking fundamentals, and a real sense of what it takes to keep a system reliable under load.
- You thrive with ambiguity and ownership. You move forward without perfect specs, make well-reasoned calls with limited oversight, and know when to stop and ask.
- You are practical about AI. You already use it to automate toil, improve data quality, and ship faster — and you have opinions about where it helps and where it doesn't.
- You care about craft. Clean, testable code; documentation the next person can actually use; systems you'd be happy to hand off.
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
- This team operates within the Central European and GMT time zone for collaboration.
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