Data Trust & AI Governance Lead

What you'll do

• Establish and enforce high data quality and trust standards across the data infrastructure.
• Govern the shared canonical data foundation that powers trusted analytics and AI systems.
• Set observability, freshness, and reliability standards to proactively detect data issues and meet SLAs.
• Manage master data, metadata, business definitions, and semantics for consistent human and AI consumption.
• Govern metric definitions and lineage to ensure source traceability and root-cause analysis.
• Enforce data standards specifically designed for reliable agentic AI and analytics readiness.
• Embed governance, quality, and observability requirements directly into data design and modernization processes.
• Establish clear ownership, stewardship, and accountability for data governance standards across the organization.

What we're looking for

• Minimum 5 years of experience in an analytics-focused role extracting insights and summarizing key findings.
• Bachelor's Degree in Math, Economics, Statistics, Computer Science, Engineering, or a related quantitative field.
• Experience establishing and operationalizing at least two core data governance functions at an enterprise level, such as data quality, observability, lineage, metadata, master data, or metrics governance.
• Master's Degree in Math, Economics, Statistics, Computer Science, Engineering, or a related quantitative field (preferred).
• Experience establishing data governance and trust for AI/ML and agentic AI, including standards for machine-consumable and grounded data (preferred).
• Experience with canonical data modeling, event and state modeling, identity resolution, and end-to-end journey data (preferred).
• Experience embedding shift-left governance into large-scale data modernization, cloud platforms, and data engineering practices (preferred).
• Proficiency in programming languages such as Python, R, and SQL with the ability to write and understand complex queries (preferred).