Senior Data Engineer

We celebrate diversity and encourage individuals of all genders (m/f/d) to apply. We're building data infrastructure that teams actually want to use. At Nelly, data doesn't just flow - it's discoverable, documented, designed with the developer experience in mind, and ultimately always serving customer needs. You'll be joining at a pivotal moment: we have working infrastructure, and we're refining it from "functional" to "exemplary." This means hardening our ingestion pipelines, building and maintaining a solid data warehouse, establishing data contracts, and implementing documentation practices where data models evolve thoughtfully. We're forming a dedicated data engineering stream within our Core Data team - and you'll be a key contributor shaping how we build and scale it. This isn't a role about moving data from A to B. It's about making data infrastructure reliable, well-documented, and developer-friendly. If you care deeply about data quality, reliability, and enabling teams to trust the data they work with, this is your opportunity to build it right. About Nelly We are a Tech Company and we believe healthcare should feel a lot less like paperwork… and a lot more like people. So we’re building the technology that lets medical practices run smoothly, simply, and without all the admin chaos that slows everyone down. Our platform turns messy processes into smart, automated workflows, from patient journeys to billing to next-generation payments. Powered by AI, built for real humans, and designed to give medical teams the time and headspace they desperately need. Why? Because Europe is facing a massive shortage of medical assistants. And if we don’t rethink how practices operate, the system won’t be able to keep up. We’re here to fix that, not with band-aids, but with real transformation. We’re backed by €50M in Series B funding from world-class investors and are scaling fast to build Europe’s leading healthcare fintech. Our vision: empower over a million medical practices and make life better for millions of patients. But here's the part we’re proudest of: we only work with nice people . It’s our number-one rule. No egos, no drama, no jerks. Just kind, curious, hardworking humans building something meaningful together. If that sounds like your kind of place - welcome to Nelly. Joining us you will Own and evolve our data pipeline infrastructure - designing and maintaining reliable, scalable ingestion and transformation pipelines across our practice management systems landscape and internal sources Own our data warehouse: drive thoughtful data modeling, ensure high data quality, and make it a trusted foundation for the Analytics and product teams who depend on it Define and enforce data contracts with producing teams, ensuring schema stability, clear ownership, and reliable data delivery Drive data model evolution: managing schema versioning, breaking change processes, and communicating impact clearly to consuming teams Build and maintain Reverse ETL pipelines to sync curated data back into operational systems and tools used across the business Establish monitoring, alerting, and incident response practices for our data systems, ensuring high availability and fast time-to-recovery Drive documentation culture around data - catalog, lineage, and metadata as first-class concerns, supporting governance and compliance in a regulated healthcare environment. Partner closely with the Data Analytics, Product and Engineering streams to ensure data is structured, accessible, and trustworthy for downstream analysis and reporting What you'll bring Strong software engineering experience in Python with production-grade data pipeline experience. Hands-on experience building and maintaining data warehouses and implementing data contracts between teams Experience with data transformation and modeling, working with both structured and semi-structured data sources Practical experience with Reverse ETL Experience with data model evolution: versioning strategies, migration processes, and maintaining backward compatibility across consumers Strong experience with AWS Experience with Kafka or similar event streaming platforms Experience implementing monitoring and observability for data systems Experience working with messy, heterogeneous data sources Experience working in regulated environments with security and compliance requirements is a strong plus Deep passion for documentation and knowledge sharing - you've championed documentation-first practices and believe undocumented data is nearly useless Nice to have Familiarity with Dagster or similar workflow orchestration tools. Exposure to data catalog tooling. Some experience or familiarity with AI/ML use cases - making data accessible for both real-time consumption and offline model evaluation. We're not hiring for this today, but it's something we'll grow into.