Data Governance Analyst

The Data Governance Analyst supports Royal Caribbean Group’s enterprise data governance programs by advancing the maturity of the enterprise data catalog and helping operationalize the data stewardship model. This role is responsible for documenting trusted data assets, maintaining high-quality business and technical metadata, improving glossary definitions, supporting lineage and ownership standards, monitoring data quality, and coordinating stewardship workflows across business and technology teams. The position also supports data privacy compliance, guest data inquiries, reporting, process improvement, and governance-ready data practices for analytics and AI use cases. Essential Duties and

Responsibilities:
1. Data Stewardship
• Operationalize data stewardship workflows by coordinating data owner and data steward assignments, certification reviews, glossary approvals, metadata remediation, access and policy questions, and issue escalation across business and technology teams.
• Schedule and hold meetings with business stakeholders related to stewardship assignments, glossary reviews, metadata decisions, and governance approvals.
• Partner with data stewards to define critical data elements, establish data ownership and accountability, support stewardship decision-making, and report stewardship KPIs such as completeness, certification status, issue aging, and policy compliance.
• Develop and maintain business glossary standards, including common definitions, synonyms, business rules, calculation logic, acronyms, ownership, approval status, and links between glossary terms and physical data assets. 2. Data Catalog
• Maintain and enhance the enterprise data catalog as a trusted inventory of critical data assets, including tables, reports, dashboards, data products, data domains, data owners, data stewards, business terms, classifications, usage context, and approved sources of record.
• Capture, validate, and maintain business, technical, operational, and governance metadata through catalog integrations, metadata harvesting, manual curation, stakeholder reviews, and ongoing metadata quality checks.
• Support lineage documentation by mapping data movement from source systems through transformations, reports, dashboards, analytical models, and downstream data products to improve impact analysis, auditability, and trust.
• Create requirements specification documents, process flow diagrams, and business process models for data catalog, metadata, glossary, lineage, and stewardship initiatives. 3. Data Quality
• Collaborate with data stewards and business stakeholders to define data quality rules, monitor quality results, document root causes, track remediation plans, and escalate recurring or high-impact data quality issues.
• Create SQL queries, reports, and dashboards to support data quality monitoring, guest data inquiries, privacy escalations, and stewardship KPI reporting.
• Locate, define, and execute process improvement opportunities that strengthen metadata quality, data quality controls, issue resolution, and stakeholder accountability. 4. Data & AI Governance
• Partner with Legal, Privacy, Security, IT, Data Science, and business teams to operationalize responsible AI requirements, including transparency, explainability, data protection, auditability, and regulatory alignment.
• Assist with AI governance platform implementation and monitoring, including tools such as Microsoft Purview, Collibra AI Governance, OneTrust AI Governance, and Databricks Unity Catalog.
• Document and govern AI use cases, datasets, and prepare audit-ready evidence for the AI lifecycle.
• Execute data subject requests and guest research escalation requests.
• Enhance and implement processes that support privacy escalations.

Qualifications:
• Bachelor’s degree in Computer Science, Information Management or Statistics.
• 3+ years data analyst or related experience, including proficiency with enterprise governance products or software solutions.
• 2+ years supporting governance, stewardship, quality, delivery, or lifecycle management of enterprise data products, data domains, or critical data assets.
• Experience supporting enterprise data catalog, metadata management, data stewardship, data quality, business glossary, lineage, ownership, certification, and governance workflow initiatives.
• Practical experience working with business data owners, data stewards, data engineers, analysts, privacy teams, and technology partners to document trusted data assets and resolve metadata or data quality issues.
• Working familiarity with catalog and stewardship platforms such as Collibra, Microsoft Purview, Alation, Databricks Unity Catalog, or similar enterprise tools.
• Familiarity with responsible AI governance frameworks and standards such as the NIST AI, ISO/IEC 42001, EU AI Act readiness, and policy controls. Knowledge and

Skills:
• Working knowledge of the Data Management Association (DAMA) framework, including the ability to apply its data management principles to support enterprise data governance, stewardship, data catalog, metadata, data quality, and lineage initiatives.
• In-depth knowledge of data stewardship practices, including domain stewardship, critical data element management, data owner engagement, business glossary governance, data quality rule definition, issue remediation, stewardship dashboards, and KPI reporting.
• Fluent with knowledge of data catalog operations, including metadata ingestion, asset registration, search and discovery, classification, tagging, ownership assignment, glossary linking, certification status, usage context, and metadata quality controls.
• Mid-level coding skills in languages such as SQL and Python.
• Mid-level proficiency in Microsoft Excel.
• Reporting and data visualization skills using software such as Power BI.