Sr Dir Data Governance

Primary Purpose of Job Family and Sub-family: The Data & AI Governance lead keeps the data value chain flowing smoothly, helping to unlock the full power of our data to drive business & customer value. The team does this by creating tools, structure, and ways of working that empower the business to make our data assets safe, secure, responsibly managed, and accessible to those who need them. Additionally, Data & AI Governance empowers the organization to responsibly leverage AI, ensuring transparency, accountability, and alignment with ethical standards. Our goal is to build trust in data and AI technologies, enabling McDonalds to enrich the customer experience and grow the customer base. Skills & Experience Required: Bachelors degree in Data Science, Information Systems, Business Administration, or a related field Masters degree or relevant certifications in data governance, AI, or related areas is a plus 15 years of experience in data governance, AI governance, or related data management roles, with at least 5 years in leadership positions Proven experience in establishing and leading data governance frameworks, responsible AI governance, and data privacy and security protocols in large organizations? Demonstrated ability to drive cross-functional collaboration, particularly with legal, compliance, IT, and business units to refine and implement governance frameworks? Extensive experience in managing risk, data quality, and controls, with a focus on operationalizing governance policies across business functions Proven leadership in fostering a culture of data literacy, accountability, and adherence to responsible data and AI practices Strong communication and stakeholder management skills, with a track record of influencing senior leadership and cross-functional teams Primary Responsibilities: Data Governance Vision & Goals: Define and implement a comprehensive strategy for data governance aligned with organizational goals and create and maintain governance structures, including councils and committees, to oversee data policies and initiatives Data Governance Frameworks (includes Tools & Enablers): Enforce data quality frameworks to maintain accuracy, consistency, and reliability of data across the organization Data Accountability Framework: Define roles and responsibilities for data stewardship, ensuring clarity on data ownership, and accountability for data quality and usage Data Privacy & Security: Establish and enforce data privacy and security policies to protect sensitive information and comply with regulations Data Quality & Controls Framework / Standards: Define data quality standards (i.e., criteria, KPIs) to ensure effective awareness, accountability, oversight, and data quality visibility across the organization Data Retention: Partner with Legal to support data retention policy definition Business Metadata Management: Identify, classify and provide context for critical data elements (how it is used, glossary / KPI definitions, etc.) Business Data Lineage: Trace and document the origin and transformation of data throughout its lifecycle within a business context Critical Data: Ensure adequate privacy and security controls on critical data such as personal information, sales data, or intellectual property (Note: Data Governance identifies critical data for less mature functions and markets today; as functions/markets reach maturity, this accountability should transition to relevant technology delivery teams) AI Governance & Ethical Frameworks : Develop governance frameworks for the ethical use of AI, ensuring alignment with industry standards and best practices Culture and Training: Foster a culture of data governance and responsible AI through training and awareness initiatives across the organization Cross-Functional Collaboration: Work with legal, compliance, and business units to ensure cohesive implementation of governance policies Financial Management: Accountable for budget, performance, and results of large, complex, or strategically diverse teams that typically span multiple locations and include global responsibilities for multiple functional areas or business units Talent & Performance Management: Responsible for management of teams including performance planning & evaluations Impact: Corporate Impact - Directly influences the achievement of operational goals of a team Communication: Level of Skill: Negotiate important agreements that have long-term, strategic implications for the entire organization Primary Audience: Internal Nature of Interaction: Engages in communication with individuals who possess varying perspectives and objectives that are divergent, potentially hindering the achievement of a solution Innovation: Level of Skill: Change significantly by enhancing entire existing processes, systems and/or products Complexity: Innovation is difficult; problems and issues may be only vaguely defined and require understanding & consideration of other disciplines and job areas Knowledge: Knowledge: Requires advanced/well-developed skills and expertise within a specific professional discipline; ability to integrate theory & principles with organizational practices Teams: Directs more than one team, determines team structure and roles of members Geographic Breadth: All region

Location: hyderabad, IN

Posted Date: 3/11/2025