You will be the senior engineering contact for the lakehouse layer, working with teams in several countries and domains.
You will coordinate 25+ data engineering and data science professionals and work alongside platform architects, data scientists, governance teams and functional IT.
The business supplies industrial materials for off-highway, rail, road, air, food, furniture and industrial applications. It has about 20,000 employees at more than 60 sites and sales of about €6.0 billion in 2025, with core branches in Asia, Europe, and North and South America.
The parent group was founded in 1871, had sales of €19.7 billion in 2025, and employs about 78,000 people in 54 countries and markets.
Responsibilities
Set the enterprise standards for data and analytics modeling, including 3NF and warehouse modeling, and for performance within the Databricks lakehouse.
Maintain and review shared enterprise data and analytics models and artifacts, and keep naming and metadata aligned with governance rules.
Drive reuse and consistent integration of core artifacts across all business domains.
Guide partitioning, indexing and performance tuning.
Build and steer semantic integration with Power BI, live tabular exploration and other tools, and own shared functions such as FX conversion, BOM logic and time-slicing.
Review and approve core components for quality and reuse, and help resolve high-performance or high-complexity problems.
Make sure lakehouse work follows architectural decisions and act as design authority for warehouse, semantic modeling and advanced analytics integration.
Work with data science and AI teams on model deployment and on bringing ML and AI pipelines into the lakehouse, including LLM and external API patterns.
Build and maintain shared libraries and engineering templates, coach junior engineers, and set TDD and as-code standards.