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.
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Own our pipelines end-to-end, from stakeholder metric definition through dbt modeling, QA, and A/B testing, to Dagster scheduling and production.
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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.
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Keep our steering metrics real and trusted as governed metrics-as-code.
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Run the relevance and content pipelines that keep the platform a reflection of real life.
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Work closely with Product, engineering, and other stakeholders to translate their data needs into models that hold up in production.
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Keep our data governance in good shape in terms of quality, security, and compliance.
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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
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Experience in a data engineering role or similar, with a solid understanding of data warehousing and ETL concepts.
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Strong SQL skills and hands-on experience running dbt models in production.
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Experience with an orchestration tool - we use Dagster.
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You've built and run data or information infrastructure that other teams depend on.
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You're comfortable working directly with backend and infrastructure engineers as well as non-technical stakeholders, and can translate between the two.
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Experience with a cloud data warehouse, ideally Snowflake, and a cloud provider, ideally AWS.
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You're comfortable with version control, ideally Git.
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You have experience working with AI coding tools like Claude Code, and know how to use them to move faster without cutting corners.
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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
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You've taken a ranking or recommendation pipeline through to production.
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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.
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You have experience or are interested in working with data agents and making them reliable.
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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.
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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...
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Communicates clearly, and can explain complex data concepts to technical and non-technical people alike.
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Keeps up with new tools and trends in the field, and likes sharing what they learn with the team.
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Values diversity, collaboration, and inclusion, and helps build a team where everyone feels welcome.
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Is a systems builder at heart - energized by building what makes everyone else faster and more certain, not by owning a queue.
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Takes ownership of unsolved problems, like safe AI access to information, rather than waiting for someone else to solve them.
What we offer
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A hybrid work model that combines at least 2 office days and remote work
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A meaningful job - we're creating a great product with real added value for the community
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Work in a cheerful and experienced team that exchanges ideas and learns from each other
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Insights into the entire work process of our social startup and the nebenan.de foundation
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Responsibility and great opportunities to actively contribute
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Your nebenan.de SpenditCard - you'll receive an additional income of 35 Euros per month, which you can use for things of your choice
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30 days of vacation per year - we also offer the possibility of workation models and a sabbatical
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