We are hiring a Senior Data Pipeline Engineer to build and own our data ingestion infrastructure. This is not a support role. This is the person who owns the data backbone of the company.
We already have a working data infrastructure built over more than a decade in the music industry, with production pipelines, crawlers, and integrations feeding real products today. Our AI agents will use this data to scout artists, model deals, forecast revenue, and automate operations. Every insight, every recommendation, every automated decision starts with data that flows through the systems you will own.
Your job is to take what exists, make it yours, and scale it. Improve reliability, expand coverage, add new sources, and evolve the architecture as we grow. You will also design and build new pipelines where needed. The foundation is solid. What we need is the person who takes it to the next level.
This is a high-ownership hire. You will work closely with product and engineering, shape how we collect and process external data, and have real architectural authority from day one.
Must have:
-
5+ years of experience building data pipelines and/or web crawling infrastructure in production environments
-
Strong Python skills: Scrapy, BeautifulSoup, Selenium, Playwright, or equivalent
-
Experience with pipeline orchestration tools such as Airflow, Prefect, or Dagster
-
Solid understanding of databases (PostgreSQL, MongoDB, or similar) and data modeling
-
Experience handling messy, inconsistent real-world data and building validation layers around it
-
Comfort with cloud infrastructure (AWS, GCP, or Azure)
-
A track record of building systems that run reliably without constant supervision
-
Deep familiarity with AI tools and workflows. AI should already be part of how you work every day. You are joining an AI-native company building AI-powered products.
Nice to have:
-
Experience with headless browsers and anti-detection techniques at scale
-
Familiarity with the music industry, streaming platforms, or media data
-
Experience with data warehousing (BigQuery, Snowflake, Redshift)
-
Exposure to message queues (Kafka, RabbitMQ, Redis)
-
Experience building internal tooling and dashboards
You think in systems, not scripts. You have built crawling or data ingestion infrastructure at a company where external data was a core input to the product, not a side project. You have dealt with the ugly realities: sites that change layouts overnight, anti-bot systems, rate limits, inconsistent APIs, and missing data. You have owned pipelines end to end.
You are self-directed. You make architectural decisions, not just execute tickets. You care about data quality almost obsessively. You are the kind of person who builds three validation checks where one would be "fine."
-
Your pipelines feed the AI agents that run scouting, deal modeling, royalties, release planning, and marketing for our clients.
-
You inherit a working data infrastructure built over more than a decade and make it yours.
-
We rebuilt the entire tech stack from scratch. No legacy to work around.
-
Small but highly skilled team. Your work ships fast and touches everything.
-
Remote-friendly with flexible hours. Office available in Zurich for those who prefer it.
Send your CV and a brief note describing a data pipeline or crawling system you built from scratch. We want to hear what scale it operated at, what broke, and how you fixed it.
Label OS is the platform independent labels use to run their business. Distribution, royalties, analytics, release operations, deal modeling, scouting, marketing intelligence. Labels use Label OS to manage their catalog, track revenue, and make better decisions without building large teams to do it.
Our AI agents will handle the repetitive work across every department so the people can focus on what actually matters: finding artists and building careers.
Our clients include some of the most respected names in independent music. We are a small, senior team that fully leverages AI across every division. We move fast, ship real products, and are building the tools that independent labels actually need to compete.
