Lead Analyst - Data & AI Governance

Why Michels?

We are consistently ranked among the top 10% of Engineering News-Record’s Top 400 Contractors.
Our steady, strategic growth revolves around a commitment to quality.
We are family owned and operated.
We invest an average of $5,000 per employee on training each year.
We reward hard work and dedication with limitless opportunities.
We believe it is everyone’s responsibility to promote safety, regardless of job titles.
We offer a comprehensive benefits program including (depending on your positions and location you may participate in a different benefit plan):
Health, Dental, Life, Flexible Spending Accounts, Health Savings Account, Short Term and Long-Term Disability Insurance, 401(k) plan, Legal Plan, and Identity Theft and Monitoring Plan

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.