OverviewThe Director, Data Governance and Enablement is responsible for architecting the frameworks, policies, and standards that ensure enterprise data is high-quality, secure, and compliant. This role bridges the gap between technical data teams and business units by driving Data Literacy initiatives-designing programs that empower employees to find, understand, and analyze data to foster a data-driven culture. You will be accountable for directing data standards, governance, and master data management to drive business value and operational efficiencies.
Duties & Responsibilities- Governance Framework: Develop, implement, and enhance a comprehensive data governance framework, including data policies, standards, and processes.
- MDM Architecture & Integration. This person must define the technical roadmap for our master data hubs, including real-time vs. batch integration and the orchestration of data across our ERP, CRM, and Google Cloud Platform environments.
- Data Architecture: Implements the rules into systems (API validation, schema constraints, lineage).
- Data Stewardship: Establish and lead a Data Stewardship program, collaborating with department heads to identify, train, and support data stewards. Enforces the rules and maintains the "Golden Record."
- Business Process Engineering & Mapping: the ability to audit how data is captured and recommend improvements to business processes
- Quality & Standards: Defines the rules and standards (e.g., "Email must be unique"). Define data quality metrics and oversee the monitoring and remediation of issues; plan and direct data cleanup and standardization efforts.
- Asset Management: Maintain the enterprise data catalog and business glossary to ensure a "single source of truth" for definitions and metadata
- Compliance & Security: Collaborate with Legal and IT to ensure data privacy (GDPR, CCPA, etc.) and security standards are met.
- Literacy & Training: Assess organizational data literacy, identifying skill gaps and delivering tailored training programs, workshops, and resources.
- Strategic Collaboration: Partner with corporate functional teams and Field Business Units to implement processes, challenge the status quo, and identify opportunities for data enrichment.
- Technical Enablement: Collaborate with IT on technology improvements that enforce data governance and lead the day-to-day team in defining product specifications and requirements.
- Operating Model & Oversight:
- This position maintains quality through a shared KPI structure and three specific governing bodies:
- Data Quality Council: (Chaired by this Director) to set enterprise standards.
- MDM Steering Committee: (Joint ownership) to drive cross-functional alignment.
- Architecture Review Board:(Chaired by Data Architecture) to ensure technical compliance.
- Project Leadership: Manage the lifecycle of large-scale data projects, including defining goals, tracking milestones, and managing budget status.
- Culture Building: Create "Data Communities of Practice" and develop communication strategies to celebrate data wins and promote evidence-based decision-making.
Candidate RequirementsEducation- Bachelor's degree in Data Science, Information Management, IT, Statistics or related field OR equivalent years of experience. Equivalent years of experience are defined as one year of applicable professional experience for each year of college requested.
Experience- State the minimum required and preferred qualifications in a clear and concise manner. If a leadership role, the experience required should be articulated.
- Minimum 10+ years of experience in data management required. With at least 5 years in MDM or Data Architecture.
- CDMP (Certified Data Management Professional) or DGSP (Data Governance Services Professional) preferred.
- Experience performing root cause analysis on data and processes to identify opportunities for improvement.
- Deep understanding of metadata, master data management, data architecture, and data modeling; experience with data quality applications and tools. Experience with Master Data Management implementation styles (Consolidated, Coexistence, Centralized) and Hierarchy Management.
- Proven experience leading cross-functional internal or external (e.g., vendor) teams using IT project lifecycle methodologies.
Skills & Competencies- Technical Proficiency: Familiarity with data governance tools (e.g., Collibra, Alation, Informatica), visualization platforms (Tableau, Power BI), and basic SQL or Python. Conceptual, Logical, and Physical data modeling and API-led connectivity.
- Communication: Exceptional storytelling skills with the ability to explain complex data concepts to non-technical stakeholders at all levels.
- Leadership: Ability to lead through influence and manage change without direct authority.
- Organization: Strong program delivery skills with the ability to manage multiple demanding projects within tight deadlines.
- Instructional Design: Experience in corporate training or designing educational resources.
