The Lead Analyst for Data & AI Governance will help build Michels' enterprise governance function from the ground up. As a founding member of the Enterprise Intelligence team, this role will shape the policies, standards, operating routines, and accountability model that make data trusted, discoverable, and usable across the business. The role will also establish practical, risk-based governance for AI so Michels can move quickly on experimentation while applying stronger oversight where use cases require durability, transparency, or compliance. This role starts hands-on, laying the groundwork that lets Michels move with speed and confidence, with a clear path to build and lead the governance team as the function matures.
Key Responsibilities:- Build and operationalize Michels' data and AI governance framework: policies, standards, roles, decision rights, and operating processes.
- Establish foundational data governance across ownership, stewardship, quality, metadata, lineage, classification, and retention.
- Partner with business, operations, and IT teams to build shared ownership of governance across data and AI work.
- Create practical AI governance for use-case intake, risk classification, responsible AI review, vendor and embedded AI oversight, and monitoring.
- Facilitate the governance forums, stewardship routines, and cross-functional decisions that clarify accountability and make governance actionable.
- Develop metrics and reporting that give leadership visibility into data quality, governance maturity, AI adoption, and emerging risks.
- Grow the function over time, evolving from hands-on builder into the leader of future governance capabilities, communities, and team.
Qualifications: - Bachelor's degree in Computer Science, Information Systems, Business Administration, or a related quantitative field, or equivalent practical experience.
- 7+ years of experience in data governance, data management, technology risk, or a related discipline at enterprise scale.
- Strong command of core governance disciplines, with demonstrated ability to build and mature governance programs.
- Familiarity with modern data platforms and governance tooling such as Microsoft Fabric, Databricks, Snowflake, Collibra, Alation, Atlan, or similar technologies.
- Working knowledge of generative and agentic AI, responsible AI, and risk-based AI governance.
- Strong communication and stakeholder skills, with the ability to influence without authority, facilitate cross-functional decisions, and explain governance and risk concepts to technical, business, and executive audiences.
