Overview
The Data Governance Analyst will support the development and execution of enterprise data governance capabilities across Haskell. This role will focus on data stewardship enablement, business glossary/taxonomy development, metadata management, and emerging AI governance needs. The analyst will work closely with business and IT stakeholders to improve data quality, consistency, and trust, while supporting governance tools.
Job Responsibilities:
- Partner with business units (PMO, Finance, Operations, Safety, etc.) to define and assign data ownership and stewardship roles
- Facilitate data governance working sessions to capture business definitions, critical data elements (CDEs), and ownership
- Support the rollout and adoption of data governance frameworks, policies, and standards
- Track and report on data governance KPIs (e.g., stewardship coverage, data quality metrics)
- Conduct training sessions for business users on Data governance concepts, Metadata Tools
- Business Glossary & Taxonomy Management
- Develop and maintain enterprise data domains, subdomains, and business glossary terms
- Ensure consistent definitions across domains (e.g., Project Budget, Cost Variance, Daily Progress %)
- Manage taxonomy structure in Atlan, including domains, subdomains, and term relationships
- Collaborate with stakeholders to resolve conflicting definitions and data inconsistencies
- Metadata Management & Data Catalog Support
- Support ingestion and curation of metadata in Atlan
- Tag assets (tables, dashboards, reports) with: Domain and subdomain, Ownership and stewardship, Sensitivity and compliance classifications
- Assist with data lineage validation and documentation
- Promote adoption of the data catalog across business teams
- Help define and document data quality rules and thresholds
- Support monitoring of data quality metrics, quality controls, and issue tracking
- Partner with data teams to resolve data quality issues and root causes
- AI Governance Support (Emerging Focus)
- Assist in establishing AI/ML governance practices, including Data inputs and lineage tracking for models, and documentation of model assumptions and outputs
- Support classification of sensitive data used in AI use cases
- Help define responsible AI guidelines and controls
- Coordinate with data science and IT teams on governance requirements
- Stakeholder Engagement & Training
- Conduct training sessions for business users on: Data governance concepts, using Metadata Tools, defining business terms and data ownership
- Serve as