Data Governance Lead

Design and develop enterprise-wide data governance programs across on-premises and cloud data estates, incorporating insurance-domain best practices for policy, claims, underwriting, billing, finance, and regulatory reporting data. Define governance operating models, ownership structures, stewardship roles, data councils, and escalation mechanisms to improve accountability across business, data product, technology, and analytics teams. Develop policies and processes for data collection, storage, access, sharing, usage, quality, archival, privacy, security, technology, tooling, modeling, reporting, and visualization across insurance data assets. Establish insurance-specific data standards, naming conventions, business glossaries, data dictionaries, reference data definitions, and canonical data models to drive consistency across policy, claims, customer, producer, product, and coverage datasets. Define and implement data quality frameworks covering profiling, validation rules, completeness, accuracy, consistency, timeliness, uniqueness, exception management, issue tracking, root-cause analysis, and remediation workflows. Partner with domain owners, data product teams, actuarial, underwriting, claims, operations, compliance, and analytics stakeholders to operationalize data quality controls and improve trust in insurance reporting and decision-making datasets. Leverage Azure cloud technologies such as Microsoft Purview, Azure Databricks, Unity Catalog, Azure Data Lake, Azure Synapse, Azure Data Factory, and Azure SQL to enable metadata management, lineage tracking, access control, cataloging, and audit readiness. Use Collibra, Ataccama, Informatica Axon/EDC, Alation, or similar governance and data quality platforms to manage business glossaries, stewardship workflows, policy compliance, data quality scorecards, lineage, and governance KPIs. Support sensitive data classification and controls for PII, PHI, PCI, financial, and confidential insurance data, ensuring alignment with privacy, security, retention, and compliance requirements. Help the Data Governance Committee define governance policies, standards, metrics, adoption roadmaps, compliance checkpoints, and change management processes for enterprise data governance initiatives. Lead teams responsible for MDM implementation, data quality engineering, governance analysis, metadata management, data stewardship, and other governance-related delivery activities