MAIN TASKS

As Enterprise AI Data Platform Engineer at Geberit, you will be instrumental in preparing our data infrastructure for AI-readiness and innovation.

You will work closely with cross-functional teams to optimize data access and governance, building data pipelines and leveraging Generative AI technologies to drive efficiency - to help building a digital twin of Geberit.

1. AI Readiness:

• Ensure data readiness for AI projects by implementing scalable data infrastructure and governance protocols.
• Collaborate with business and IT stakeholders to facilitate easy and secure access to data across teams. 
• Contribute to AI experiments and implementations by connecting data sources and optimizing data flows for machine learning models, thanks to a good understanding of Geberit data and business processes.

2. Data Pipelines & Cloud Infrastructure:

• Design, build, and maintain reliable and efficient data pipelines to integrate data from multiple sources, ensuring data quality and accessibility.
• Work with Microsoft Fabric cloud technologies to build scalable data architectures suitable for AI workloads.
• Develop ETL processes to transform raw data into valuable insights, helping drive decision-making in product and manufacturing processes.

EDUCATION AND QUALIFICATION

• Bachelor's degree in Computer Science, Data Engineering, or a related field.
• 3+ years of experience in data engineering.
• Experience with data modeling, data governance, and developing data access protocols.
• Solid understanding of cloud platforms and experience with data pipeline tools in MS Fabric.
• Strong Python or SQL skills and familiarity with big data technologies.
• Knowledge of Generative AI basics, including prompt engineering, RAG systems, and working with graph databases is a plus.
• Ability to collaborate with diverse stakeholders, bridging the gap between IT and business.