We are looking for a:

Data Engineer (all genders)

We're not looking for tool operators. We're looking for someone who understands data, uses AI as a tool, and knows what's behind it.
AI is changing the way we work, but good solutions still arise from understanding, experience, and critical thinking.
You actively use AI to improve, not to delegate responsibility. You know when a code generator or copilot is helpful and when it leads us astray. You question results, recognize errors, and take ownership of your solutions.
Your role:
As a Data Engineer (all genders), you develop data solutions that connect our systems and transform data into reliable information.
You don't think of data in isolation, but as part of a larger context. You strategically use modern AI tools to work more efficiently, develop better solutions, and further develop processes.
You're someone who doesn't just ask, "Does this work?" but also, "Is it the right solution?"
Your tasks

• Design, develop, and operate data pathways between systems
• Develop, optimize, and secure ETL and ELT processes
• Analyze and connect data sources (e.g., ERP, CRM, APIs, cloud systems)
• Designing data models for reporting, BI and operational processes
• Analyze and sustainably resolve errors in data processes
• Actively shape and develop data architecture
• Use AI tools specifically for code generation, documentation, and analysis.
• Specialist departments, BI and IT as technical contact persons

AI as a tool:
You use LLMs, Copilots, and AI tools strategically to work faster and better. At the same time, you know where AI provides support—and where your own technical understanding is required.
Business judgment:
You critically evaluate AI-generated code, data models, and transformations and take responsibility for the results.
Systems thinking:
You understand data flows as part of larger processes and recognize connections between technology, business expertise, and organization.
Continuous learning:
You remain curious and continue to develop. AI and technologies are changing rapidly. You learn purposefully and with a focus on practical application.
We are tool-agnostic. For us, it's not the tool that matters, but that you understand the concepts behind it.
Possible technologies:

• SQL / T-SQL
• Python
• REST APIs / JSON
• ETL/ELT concepts
• Azure Data Factory
• Microsoft Fabric
• SSIS
• Apache NiFi / Spark
• Git / CI / CD
• Power BI
• KI-Coding-Tools
• LLM-supported documentation
• Prompt Engineering

What you bring

• Experience in data engineering, data integration, or database development
• Excellent SQL skills and understanding of data modeling
• Experience with data flows, interfaces and ETL/ELT processes
• Active use of AI tools in everyday work – not just for experimentation.
• Ability to critically evaluate AI-generated results
• Enjoyment in understanding and explaining complex technical relationships
• Independent learning willingness and interest in new technologies

You don't need to be an AI specialist. What's important is that you use AI wisely and know its limitations.