Head of Data Governance At Nielsen, we believe that career growth is a partnership. You ultimately own, fuel and set the journey. By joining our team of nearly 14,000 associates, you will become part of a community that will help you to succeed. We champion you because when you succeed, we do too. Embark on a new initiative, explore a fresh approach, and take license to think big, so we can all continuously improve. We enable your best to power our future. The Head of Data & Analytics Governance is a critical leadership role responsible for establishing and maintaining a robust data and analytics governance framework within the organization. This individual will champion data quality, integrity, security, and compliance across all business units, ensuring data is treated as a valuable business asset and managed effectively. Whilst there are pockets of high maturity data management practices through the business, there is a need for the establishment of an enterprise wide data and analytics governance program as a business capability. In the future there may also be opportunities to extend this role into the domain of AI governance given the importance of data in the responsible and productive use of AI technologies. The successful candidate will use their skills, influence, and experience to establish and lead high performing teams, engage stakeholders and implement effective frameworks for the delivery of strategies and systems aligned to the needs of the business.
Description
Stakeholder Engagement: Build and maintain strong relationships with key stakeholders, including business leaders, IT teams, and data stewards, with the goal of identifying and prioritizing business goals. See the Network section for additional details about the set of stakeholders to engage with.
Develop and Implement Data & Analytics Governance Framework: Define, implement, and enforce data governance policies, standards, and procedures, ensuring alignment with business objectives and regulatory requirements. This is the primary responsibility; the points below are all in support of this primary responsibility.
Operating Model for Data & Analytics Governance: Create and implement a comprehensive operating model, defining roles, responsibilities, processes, and metrics to ensure effective data & analytics governance that aligns with the strategy, across the organization.
Establish Data & Analytics Governance Council: Create and lead a cross-functional Data & Analytics Governance Council to facilitate collaboration and decision-making on data-related matters.
Stakeholder Management: employ techniques to ensure stakeholders’ needs and expectations are understood and managed; potential conflicts or issues are identified and addressed early on; and build trust and foster collaboration for mutually beneficial outcomes.
Prioritization: evaluate the relative value of data & analytics governance and management initiatives by evaluating against a set of developed criteria; and ensuring that potential conflicts in priorities with stakeholder groups are discussed, evaluated and agreed collaboratively.
Data Quality Management: Collaborate with the Business as they define and monitor data quality metrics, identify and address data quality issues, and implement data cleansing and enrichment initiatives.
Data Security and Privacy: Collaborate with the Privacy team to ensure compliance with data security and privacy regulations (e.g., GDPR, CCPA), implement data access controls, and protect sensitive data.
Metadata Management: Collaborate with the Business as they establish and maintain a comprehensive metadata repository to facilitate data discovery, understanding, and usage.
Data Lineage and Traceability: Collaborate with the Business as they implement data lineage and traceability processes to track data flows and transformations, supporting regulatory compliance and impact analysis.
Data Governance Tools and Technologies: As necessary, evaluate, select, and implement data governance tools and technologies to support data profiling, quality monitoring, metadata management, and data lineage.
Change Management: Lead data & analytics governance change management initiatives, promoting data & analytics governance awareness and adoption across the organization.
Training and Education: Develop and deliver data & analytics governance training and education programs to enhance data literacy and data & analytics governance understanding.
Financial: Global COE and Internal Control metrics, Internal and External Audit observations, Adherence to closing deadlines
Values: Open, Connected, Useful, Personal
Requirements
Bachelor's degree in Computer Science, Information Management, or a related field.
This role is applicable across various industries, but experience in regulated industries (e.g., finance, healthcare) is a plus.
Relevant certifications (e.g., Certified Data Management Professional (CDMP), Certified Information Privacy Professional (CIPP)) are desirable.
Fluency in English and local language mandatory
Experience
Excellent communication, collaboration, and leadership skills.
Ability to work effectively with cross-functional teams and influence stakeholders.
High levels of energy, conscientiousness, rapport building, resiliency, inventiveness, and curiosity.
Strong understanding of data management principles, data quality, data security, and data privacy.
Expertise in managing organizational change related to technology adoption and implementing change management strategies to ensure smooth transitions.
Effective communication and collaboration with stakeholders at all levels, balancing competing priorities and managing expectations.
Experience with data & analytics governance tools and technologies.
Ideally, 10+ years of experience in data management, data governance, or a related field.
Ideally, a proven track record of successfully implementing and leading data & analytics governance programs.
Ability to evaluate and manage relationships with technology vendors, including understanding contractual terms, service-level agreements (SLAs), and negotiation skills.
