Your mission

We're looking for a Data Engineer to join our Information and AI Platform and own our data pipelines end to end — from data modeling to experimentation to production.

• Own our pipelines end-to-end, from stakeholder metric definition through dbt modeling, QA, and A/B testing, to Dagster scheduling and production.

• Move us from people asking for reports to a system that answers — self-service for coworkers, reliable answers for AI agents, a self-describing warehouse.

• Keep our steering metrics real and trusted as governed metrics-as-code.

• Run the relevance and content pipelines that keep the platform a reflection of real life.

• Work closely with Product, engineering, and other stakeholders to translate their data needs into models that hold up in production.

• Keep our data governance in good shape in terms of quality, security, and compliance.

• Work with the team to improve personalized recommendations and other ML algorithms.

Our stack: dbt, Snowflake, MotherDuck, Dagster, SQL, Python, AWS, GitHub Actions, Docker, VS Code 

Your profile

Must-haves

• Experience in a data engineering role or similar, with a solid understanding of data warehousing and ETL concepts.

• Strong SQL skills and hands-on experience running dbt models in production.

• Experience with an orchestration tool — we use Dagster.

• You've built and run data or information infrastructure that other teams depend on.

• You're comfortable working directly with backend and infrastructure engineers as well as non-technical stakeholders, and can translate between the two.

• Experience with a cloud data warehouse, ideally Snowflake, and a cloud provider, ideally AWS.

• You're comfortable with version control, ideally Git.

• You have experience working with AI coding tools like Claude Code, and know how to use them to move faster without cutting corners.

• You're sound on GDPR and Article 9 in practice — you know how to design compliant data access for both people and agents.

Nice-to-haves

• You've taken a ranking or recommendation pipeline through to production.

• You know your way around ML concepts — you don't need to build models yourself, but understanding the basics helps you work well with our ML engineers.

• You have experience or are interested in working with data agents and making them reliable.

• You're fluent in modern data and AI tooling and agentic systems, and understand why curation and semantic context decide whether agents can be trusted.

• You've led or mentored other engineers, or you're ready to grow into that, with support from our Leadership & Coaching guild.

And you're the kind of person who...

• Communicates clearly, and can explain complex data concepts to technical and non-technical people alike.

• Keeps up with new tools and trends in the field, and likes sharing what they learn with the team.

• Values diversity, collaboration, and inclusion, and helps build a team where everyone feels welcome.

• Is a systems builder at heart — energized by building what makes everyone else faster and more certain, not by owning a queue.

• Takes ownership of unsolved problems, like safe AI access to information, rather than waiting for someone else to solve them.

What we offer

• A hybrid work model that combines at least 2 office days and remote work

• A meaningful job – we're creating a great product with real added value for the community

• Work in a cheerful and experienced team that exchanges ideas and learns from each other

• Insights into the entire work process of our social startup and the nebenan.de foundation

• Responsibility and great opportunities to actively contribute

• Your nebenan.de SpenditCard – you'll receive an additional income of 35 Euros per month, which you can use for things of your choice

• 30 days of vacation per year – we also offer the possibility of workation models and a sabbatical

If we’ve captured your interest, apply now and let us know why you’re the perfect fit for the job!