Bachelor's or Master's degree in Data Science, Information Systems, Business, or related field.
10+ years of experience in data governance, analytics, or data management roles.
Proven leadership experience in building and scaling enterprise data and AI programs.
Strong understanding of data privacy regulations and AI ethics frameworks.
Expertise in data governance tools and enterprise analytics platforms.
Excellent communication, stakeholder management, and strategic thinking skills.
Responsibilities
Develop and implement a comprehensive data governance framework aligned with business objectives.
Define and enforce data policies, standards, and stewardship practices across business units.
Establish data ownership and accountability models between IT and business stakeholders.
Lead data quality initiatives and ensure compliance with regulatory requirements.
Oversee the design, development, and deployment of enterprise analytics platforms and reporting tools.
Drive the adoption of advanced analytics, including predictive modeling, machine learning, and AI.
Develop and implement an AI governance framework to ensure ethical, transparent, and responsible use of AI technologies.
Benefits
Opportunity to lead enterprise-wide data and AI governance initiatives.
Collaborative environment with cross-functional teams.
Focus on ethical and responsible AI practices.
Access to advanced data governance and analytics technologies.
Potential for professional development in a rapidly evolving field.
Full Job Description
Job Description
The Senior Director of Data & AI Governance will lead the strategic development and execution of enterprise-wide data and AI governance initiatives. This role is responsible for establishing policies, standards, and frameworks that ensure data and AI assets are managed responsibly, securely, and effectively across the organization. The ideal candidate will be a visionary leader with deep expertise in data strategy, governance, advanced analytics, and responsible AI, capable of driving business value through data-driven and AI-enabled decision-making.
Responsibilities
Data Governance Leadership
Develop and implement a comprehensive data governance framework aligned with business objectives.
Define and enforce data policies, standards, and stewardship practices across business units.
Establish data ownership and accountability models between IT and business stakeholders.
Lead data quality initiatives and ensure compliance with regulatory requirements for Environment sustainability Organization.
Analytics Strategy & Execution
Oversee the design, development and deployment of enterprise analytics platforms and Reporting tools.
Drive the adoption of advanced analytics, including predictive modeling, machine learning, and AI.
Partner with business leaders to identify opportunities for data-driven innovation and operational efficiency.
Ensure analytics solutions are scalable, secure, and aligned with enterprise architecture.
AI Governance
Develop and implement an AI governance framework to ensure ethical, transparent, and responsible use of AI technologies.
Collaborate with legal, compliance, and risk teams to align AI initiatives with regulatory and ethical standards.
Establish policies for model lifecycle management, including documentation, monitoring, and explainability.
Promote fairness, accountability, and transparency in AI systems, and mitigate risks such as bias and unintended consequences.
Lead cross-functional efforts to educate stakeholders on responsible AI practices and governance.
Data Security
Partner with cybersecurity and IT teams to ensure data protection policies are integrated into governance and analytics workflows.
Define and enforce data classification, access control, and encryption standards across the data lifecycle.
Monitor and respond to data-related security risks, breaches, and vulnerabilities.
Promote a culture of data security awareness and accountability across the organization.
Team & Stakeholder Management
Build and lead a high-performing team of data governance professionals, data scientists, and analysts.
Foster a data- and AI-driven culture across the organization through education and engagement.
Collaborate with IT, legal, compliance, and business units to align data and AI initiatives with strategic goals.
Technology & Tools
Evaluate and implement data governance and analytics technologies (e.g., Microsoft Purview, Collibra, Informatica).
Ensure integration of metadata management, data cataloging, and lineage tracking tools.
Monitor emerging trends and technologies to continuously evolve the data and AI strategy.
Qualifications
Bachelor's or Master's degree in Data Science, Information Systems, Business, or related field.
10+ years of experience in data governance, analytics, or data management roles.
Proven leadership experience in building and scaling enterprise data and AI programs.
Strong understanding of data privacy regulations and AI ethics frameworks.
Expertise in data governance tools and enterprise analytics platforms.
Excellent communication, stakeholder management, and strategic thinking skills.
Preferred Skills:
Experience in sustainability, manufacturing, or regulated industries.
Familiarity with cloud data platforms (e.g., Azure, AWS, GCP).
Certification in data governance, Cybersecurity or AI ethics (e.g., CDMP, DAMA, Responsible AI).
Strategic Leadership & Vision
Ability to set a clear vision for enterprise-wide data and AI governance.
Skilled at aligning governance initiatives with business objectives and driving organizational change.
Experience in building and leading high-performing teams and fostering a data-driven culture.
Technical Expertise in Data & AI Governance
Deep knowledge of data governance frameworks, policies, and stewardship practices.
Expertise in advanced analytics, AI, and machine learning, including ethical and responsible AI use.
Familiarity with data governance and analytics technologies (e.g., Microsoft Purview, Collibra, Informatica).
Program & Project Management
Proven capability to design, implement, and scale complex data and AI programs across the enterprise.
Strong skills in managing cross-functional projects, ensuring timely delivery, and measuring impact.
Ability to oversee model lifecycle management, data quality initiatives, and compliance programs.
Stakeholder Engagement & Communication
Excellent communication and stakeholder management skills.
Ability to collaborate with IT, legal, compliance, business units, and executive leadership.
Skilled at educating and influencing diverse audiences on data and AI governance best practices.
Risk Management & Regulatory Compliance
Strong understanding of data privacy regulations, cybersecurity, and AI ethics frameworks.
Ability to identify, assess, and mitigate risks related to data security, privacy, and AI bias.
Experience in ensuring compliance with regulatory requirements and promoting accountability.
