20 beste Stellen als product developer (m/f/d) in berlin – aktuell auf Personalsuche

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product developer (m/f/d) jobs near berlin

Senior Data Engineer

Nelly Solutions
Berlin

Direkt bewerben

Details zur Stelle

Vollzeit
vor 2 Tagen

Qualifikationen

AWS
Kafka
Künstliche Intelligenz
Python

Vollständige Stellenbeschreibung

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.

Direkt bewerben

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