* Govern the enterprise-wide standards for data & analytics modeling and performance within the Databricks Lakehouse.
* Drive consistency and reuse of core data & analytics artifacts and ensure scalable integration across all business domains.
* Provide expert consulting, quality assurance, and enablement for data engineering and data science teams.
* Act as a design authority for data warehouse, semantic modeling, and advanced analytics integration.
* Acts as the senior engineering point of contact for the lakehouse layer across global teams.
* Coordinates with 25+ data engineering and data science professionals across domains and geographies.
* Collaborates closely with platform architects, data scientists, governance teams, and functional IT globally.
Main Tasks:
• Define enterprise 3NF and warehouse modeling standards.
• Maintain and review enterprise-wide data & analytics models and shared artifacts.
• Align naming conventions and metadata handling with governance standards.
• Guide partitioning, indexing, and performance tuning.
• Enable, steer and optimize semantic integration with Power BI, live tabular exploration and other tools.
• Own common functions, e.g. FX conversion, BOM logic, time-slicing.
• Review and approve core components for quality and reusability.
• Provide support on high-performance or high-complexity challenges.
• Align lakehouse implementation with architectural decisions.
• Collaborate with data science and AI teams on model deployment.
• Ensure seamless integration of ML/AI pipelines into the lakehouse.
• Support LLM and external API integration patterns.
• Build and maintain shared libraries and data engineering templates.
• Coach junior engineers and define TDD and "as-code" standards.
• Drive engineering excellence across the community of practice.
• Maintain architectural blueprints, templates, and best practices.
• Publish design guidelines and coding standards.
• Create re-usable architecture patterns for lakehouse environments.
• Monitor usage and implement auto-scaling policies.
• Analyze and optimize cluster configurations for cost-efficiency.
• Provide cost transparency and usage reporting to stakeholders.
continental