Head of Data Management and Governance

Location: Portugal / Germany | Remote

Körber - Data & Analytics Platform Team

We're looking for a Head of Data Management and Governance to lead and inspire the Data (Governance) Engineers, establish Data Governance as a central discipline, and ensure the success of ML/AI and data initiatives across Körber. You will shape the data strategy, foster a data-driven culture, and collaborate closely with the Data Platform team and company domains.

Key Responsibilities

• Provide a strategic positioning of DG in the Körber Group
• Establish Data Governance as central and impactful discipline, e.g., by initiating central committees and best practice exchanges
• Lead and inspire a team of Data (Governance) Engineers
• Deepen and broaden the content of the existing Data Governance framework and federate it in context of a data mesh implementation
• Govern data and ML/AI models in Körber’s data platform by creating policies, formalizing roles, and assigning responsibilities
• Assist the company domains in conceptual and practical implementation of DG standards and manage the corresponding user community
• Create new and improve existing data products in collaboration with their data product owners and consumers
• Contribute to the creation of a Körber-wide data strategy and emerging sub-initiatives
• Oversee and consult on the implementation of ML/AI use cases from a data science perspective to foster success and compliance with the DG framework
• Partner with the Data Platform team to foster an active adopter community, guiding onboarding and encouraging ongoing participation

Required Skills & Experience

• Having led a team of individuals with heterogeneous expertise
• Having worked in the realm of data governance (frameworks, policies, compliance) or MLOps, e.g., translating legal requirements into guidelines and policies
• Having hands-on experience with Microsoft Azure Tool Suite and Databricks for data processing
• Having participated in the creation of a data strategy or its operational implementation

Technical Skills

• Structuring work items for yourself and others, deriving concrete actions from abstract concepts, and prioritizing stakeholders’ needs
• Implementing Data Scientific / Engineering components in Python
• Educating yourself and others in applying new technologies and tools
• Building and supporting active user communities