Data Governance Leader - Enterprise Data & AI Enablement

Job Information

The Data Governance Leader is expected to establish, operationalize, and lead enterprise data foundations that support both AI capabilities and traditional reporting/analytics. This role is responsible for ensuring data – structured, semi-structured, and unstructured - is trusted, well‑defined, discoverable, secure, and ready for consumption.

Success in this role requires building practical frameworks, clear ownership models, and repeatable practices that enable teams to move fast with confidence and effective risk management.

Role & Responsibility

1. Enterprise Data Governance Strategy

• Define and own the enterprise data governance strategy spanning structured, semi‑structured, and unstructured data
• Design, document, and reinforce enterprise data usage practices including data definitions, quality expectations, lineage transparency, and access controls so Bobcat teams can effectively consume data for AI, analytics, dashboards, and operational reporting.
• Work closely with Legal and risk management teams to support data privacy and compliance requirements while reinforcing innovation, speed, and usability
• Ensure strategic alignment with Bobcat’s Enterprise Master Data Management team initiatives

2. Enable AI‑Driven Data Use

• Partner with AI Center of Excellence and Digital teams to ensure data inputs and outputs are traceable, explainable, and trusted
• Work directly with AI and analytics builders to ensure data is used responsibly, efficiently, and at enterprise scale by:
  • Applying data classification standards to AI use cases so teams understand what data can be used, how, and under what conditions
  • Identifying data‑related risks early (e.g., privacy, sensitivity, misuse, localization) and guiding teams toward compliant design choices
  • Surfacing opportunities to streamline data usage, reducing redundant data pipelines, duplicate feature engineering, and inconsistent approaches
  • Shaping globally scalable data designs, ensuring AI solutions account for regional data requirements, reuse patterns, and future expansion

3. Shape Structured & Unstructured Data Practices

• Design and maintain enterprise approaches for identifying and capturing business definitions, metrics logic and semantic consistency
• Define how different data types are classified, owned, accessed, and refreshed
• Work with Bobcat teams to successfully implement defined data practices

4. Clarify Ownership & Decision Rights

• Establish clear accountability and operating model across data domains aligning business, AI and Digital stakeholders to maximize the value of Bobcat’s data
• Embed data accountability into delivery teams and workflows

5. Drive Adoption & Change

• Connect and build trusted relationships with key stakeholders from various Bobcat Lines of Business 
• Lead awareness and enablement sessions so Bobcat teams understand how to classify and use data responsibly and effectively
• Replace policy‑heavy approaches with clear guidance, examples, and tooling alignment
• Put mechanisms in place to identify, surface, and address data quality issues
• Track and demonstrate impact through improved trust, reuse, and decision quality

Job Requirement

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
• 10+ years in data, analytics, AI, or information management roles
• Experience establishing data governance policies and designing secure, high-availability data systems.
• Proven expertise in building and operating enterprise data frameworks
• Experience in the identification and management of metadata and data lineage
• Strong understanding of analytics platforms, semantic layers, and reporting ecosystems
• Comprehension of unstructured data usage in AI and knowledge systems
• Strong leadership, change management, mentoring, and communication skills with a track record of influencing cross-functional teams

Preferred Requirements

• Prosci or equivalent change management certification
• Snowflake and dbt experience
• Agile development experience
• Ability to balance immediate business needs with long-term strategic data architecture goals
• Travel: <25%