Principal Analyst, Data Governance and AI Readiness
About The Position
The Principal Analyst, Data Governance and AI Readiness defines, implements, and enforces data governance frameworks so enterprise data is well-understood, shareable, standardized, and ready for AI. The role works directly with the Senior Manager, Data Strategy and leads governance initiatives for Finance data, including metadata management, data lineage, catalogs, semantic models, and data products. It establishes reusable standards and governance practices, resolves complex issues, and communicates outcomes, risks, and investment needs to senior leadership. The position partners with technical and business teams to develop consistent, machine- and human-readable data meanings and metric definitions aligned with business objectives. It facilitates governance councils and stakeholder discussions, translates between technical and business concepts, identifies governance gaps, and ensures solutions use approved definitions, semantic models, certified data products, and authoritative metadata. The role also supports regulatory and compliance needs and may mentor junior analysts as the team grows.
Requirements
- Bachelor’s degree in Information Systems, Data Management, Business, or a related field.
- At least 5 years of progressive experience in data governance, data management, data architecture, analytics, AI governance, or a related discipline, including demonstrated leadership of complex cross-functional initiatives in a large enterprise.
- Strong understanding of data governance frameworks, such as DAMA-DMBOK.
- Experience with semantic models, metadata management, and master/reference data.
- Familiarity with data privacy and regulatory compliance requirements.
- Excellent communication skills and ability to influence without formal authority.
- Proven ability to work across business and technical teams.
Nice To Haves
- Master’s degree or relevant certifications, such as CDMP or DGSP.
- At least 7 years of progressive experience in data governance, data management, data architecture, analytics, AI governance, or a related discipline.
- Experience with data governance tools such as Collibra, Alation, Informatica, or Purview.
- Familiarity with Finance data.
- Experience with SQL, dbt, Alteryx, Tableau, or similar languages and packages.
- Data analysis skills.
- Experience in agent orchestration.
- Experience in large, complex, or highly regulated environments.
Responsibilities
- Lead metadata management, data lineage, and data catalog initiatives, using agents to maintain a holistic and current view of Finance data governance artifacts.
- Define and operationalize governance policies, standards, decision rights, and minimum controls for data products, metadata, lineage, semantic models, data quality, access, and lifecycle management.
- Resolve complex governance issues and competing stakeholder priorities through structured decision-making, escalation, and risk-based recommendations.
- Establish measurable governance outcomes and adoption indicators, and communicate progress, risks, dependencies, and investment needs to senior leadership.
- Create reusable governance frameworks, standards, implementation patterns, and reference materials for adoption across data domains and delivery teams.
- Lead complex cross-functional initiatives where requirements, ownership, technology direction, or operating models are not fully defined.
- Influence development of a semantic layer designed for broad consumption across current and future AI projects.
- Develop standardized data meanings derived from master data and readable by people and machines.
- Partner with technical teams to create metric definitions alongside new data product development.
- Partner with business stakeholders to align data and metric definitions with business objectives.
- Facilitate data governance councils, working groups, and stakeholder meetings.
- Translate technical data concepts into business-friendly language and business concepts into technical language.
- Identify governance gaps and recommend pragmatic, scalable solutions.
- Ensure solutions use governed business definitions, approved semantic models, certified data products, and authoritative metadata instead of independently recreating or inferring business logic.
- Support regulatory and compliance requirements, including GDPR, SOX, CCPA, and HIPAA.
- As the team grows, mentor junior analysts and serve as a subject-matter expert in data governance best practices.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
