IT engineer Data Lakehouse - Tech Lead

* 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.

Degree in Computer Science or related field; certifications in Databricks or Microsoft preferred.

6–10 years in data engineering with focus on enterprise data & analytics warehouse, lakehouse modeling, and ML integration.

Hands-on experience designing large-scale semantic, warehouse, and advanced analytics layers.

Track record of architectural ownership and peer enablement with diverse teams.

Experience working in international teams across multiple time zones and cultures, preferably with teams in India, Germany, and the Philippines.

The well-being of our employees is important to us. That's why we offer exciting career prospects and support you in achieving a good work-life balance with additional benefits such as:

• Training opportunities
• Mobile and flexible working models
• Sabbaticals

and much more...

Sounds interesting for you? Click here to find out more.

Diversity, Inclusion & Belonging are important to us and make our company strong and successful. We offer equal opportunities to everyone - regardless of age, gender, nationality, cultural background, disability, religion, ideology or sexual orientation.

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