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!

Jobs at Good Hood Gmbh

Job recommendations