Data Governance Lead - 75k, Logistics

Key Responsibilities

• Lead the execution, adoption, and continuous improvement of enterprise-wide data governance frameworks, policies, standards, and operating procedures across business functions and geographical regions.

• Drive governance from strategy into day-to-day operations by establishing clear ownership, accountability, and governance processes for critical data assets.

• Manage, mentor, and develop a team of Data Governance Specialists, setting priorities, allocating resources, and ensuring the successful delivery of governance initiatives and operational activities.

• Facilitate and chair Data Governance Council and working group meetings, ensuring decisions are documented, action plans are implemented, issues are escalated appropriately, and outcomes are tracked to completion.

• Own enterprise data quality and master data governance practices, overseeing data quality monitoring, issue remediation, root-cause analysis, and continuous improvement initiatives to enhance business and analytical outcomes.

• Partner with business stakeholders, data owners, data stewards, technology teams, and analytics functions to embed governance controls into business processes and data lifecycle management activities.

• Drive the adoption of data governance best practices, including metadata management, data lineage, data classification, stewardship models, and data quality standards.

• Ensure compliance with applicable data privacy, security, regulatory, and risk management requirements by collaborating closely with Technology, Information Security, Risk, Compliance, and Legal teams.

• Oversee governance controls across data and analytics platforms, including data access management, usage monitoring, policy compliance, and data asset transparency.

• Define and monitor governance KPIs, data quality metrics, and stewardship performance measures, providing regular reporting to senior leadership and governance committees.

• Promote a data-driven culture through data literacy initiatives, stakeholder engagement, training programs, and governance awareness activities.

• Support the organization's data transformation and AI initiatives by ensuring trusted, high-quality, and governed data assets are available for business decision-making.

Requirements

• Bachelor's degree or above in Information Management, Computer Science, Data Analytics, Business, or a related discipline.

• 10-15+ years of experience in data management, data governance, data quality, master data management (MDM), or analytics governance within large-scale multinational organizations.

• Proven track record of implementing and operationalizing enterprise data governance frameworks, standards, and controls across complex business environments.

• Strong expertise in key data management disciplines, including:

  • Data Governance
  • Data Quality Management
  • Master Data Management (MDM)
  • Data Stewardship
  • Metadata Management
  • Data Lineage
  • Data Lifecycle Management

• Hands-on experience establishing governance operating models, ownership structures, and accountability frameworks across business and technology stakeholders.

• Good understanding of data privacy, information security, regulatory, and risk management requirements, with experience translating policies into practical operational controls.

• Demonstrated people leadership experience, including managing governance, data management, or data quality teams within matrixed and global organizations.

• Strong stakeholder management skills with the ability to influence senior business leaders, technology teams, and executive stakeholders.

• Experience working with modern data and analytics platforms, data catalog tools, data quality solutions, and governance technologies.

• Strong analytical, problem-solving, and execution capabilities, with the ability to balance strategic objectives and operational delivery.

• Excellent verbal and written communication skills in English; experience working in a regional or global environment is highly preferred.