Data Governance Lead

Job Title: Data Governance Lead Location: Houston, TX (4 days a week onsite from Day 1) Job Type: Contract Job Description • Proven experience operationalizing Data Governance frameworks, updating runbooks, and integrating Data & AI standards. • Ability to define data asset certification processes, enhance governance structures, and align domain/sub domain models with access management. • Skilled in formalizing and enabling Data Owner, Data Steward, and Technical Owner roles, including developing role definitions and delivering training. • Hands on experience with Atlan and Monte Carlo for configuration, integrations, lineage build out, data quality monitoring, and issue remediation workflows. • Ability to assess and improve AI/analytics tool interoperability, prioritize integrations, and establish standards aligned access and permissions. • Strong capabilities in data quality reporting, KPI creation, root cause analysis, and ongoing governance compliance reporting (including Data Health Score formulas). • Experience building and maintaining governance content hubs (e.g., SharePoint) and driving community engagement through training and enablement. • Strong communication and facilitation skills to advise and consult teams on Data Governance best practices, standards adoption, and appropriate use of data tools. • Experience supporting enterprise-wide Data Governance initiatives, including standards harmonization, cross domain alignment, and coordination across business and technical teams. • (Preferred) Familiarity with agentic AI for data cleansing, metadata improvement, and prototype/MVP delivery. • Workflow & Playbook Automation: Ability to automate governance tasks using Atlan’s API driven playbooks (e.g., bulk tagging, glossary propagation, asset certification). • Automated Metadata Enrichment: Experience using Atlan AI and agentic workflows to automate descriptions, README creation, and metadata suggestions. • GCP Integration & Migration: Expertise migrating GCP/Big Query tags into Atlan and automating the identification/prioritization of assets for ingestion. • End to End Lineage Automation: Skilled in defining methods and building lineage across diverse tool stacks, including systems without native integrations.