Operational Data Stewardship. You will perform hands-on stewardship activities for assigned data assets. Accountability is specific to assigned assets, with stewardship responsibilities measured by metadata completeness, data quality outcomes, risk reduction, and time to resolution. Define, validate, and curate business and technical metadata for assigned data assets, including business definitions, critical data elements, lineage, reference data, data dictionaries, quality rules, ownership, and approved usage context. Maintain metadata and stewardship artifacts in enterprise governance tools, including business glossary terms, data catalog entries, lineage documentation, issue records, ownership assignments, and approval workflows. Ensure metadata accuracy and completeness through regular review cycles, validation with supporting SMEs, and alignment to enterprise standards. Monitor data quality indicators, assess impacts to downstream use cases, triage issues based on severity and business impact, and coordinate remediation across business, IT, analytics, operations, product, and vendor teams. Perform or coordinate root-cause analysis for recurring or high-impact data quality issues and recommend preventive controls, process changes, ownership clarification, or system remediation. Interpret enterprise data governance policies, standards, and controls as they apply to assigned assets, including data classification, sensitivity, privacy, access, retention, and responsible use requirements. Facilitate policy exception, data access, and data use reviews by assessing risk, documenting rationale, coordinating approvals, and tracking compensating controls where required. Support trusted data use for reporting, analytics, data products, automation, and AI-enabled initiatives by ensuring assigned assets are well-defined, quality-monitored, traceable, and aligned to approved business context. Actively participate in domain-based governance and stewardship working groups, representing assigned data assets and escalating risks, decisions, and improvement opportunities. Partner with Data Owners, Product Owners, Architects, and domain leaders to align stewardship priorities to domain roadmaps and enterprise initiatives. Enterprise Stewardship Enablement. Collaborate with department leaders, analysts, system owners, SMEs, and technology partners to promote stewardship practices across the enterpriseSupport the development and continuous improvement of stewardship standards,, procedures, templates, intake processes, escalation paths, role definitions, and performance measures. Help mature the enterprise stewardship operating model, including RACI alignment, decision rights, governance forums, stewardship workflows, and issue-management practices. Facilitate knowledge sharing and help socialize stewardship roles, responsibilities, standards, and processes across teams. Contribute to the scaling of an enterprise data stewardship community through training, documentation, onboarding materials, process guidance, and practical examples. Compile and analyze data quality metrics and stewardship KPIs; produce reports and insights to highlight trends, risks, gaps, and improvement opportunities. Conduct benchmarking, maturity assessments, stakeholder feedback reviews, and other evaluations to identify emerging data governance needs or gaps. Provide strategic recommendations to leadership on data quality risks, governance priorities, stewardship, and opportunities to advance enterprise data effectiveness. Cross-Functional Collaboration & Leadership. Partner with project teams to ensure data governance, data quality, metadata, privacy, security, and responsible-use principles are integrated into system implementations, enhancements, migrations, reporting solutions, and workflows. Participate in or lead governance working groups, stewardship forums, data asset reviews, quality issue reviews, and cross-functional problem-solving sessions. Facilitate discussions with business and technical stakeholders to resolve ambiguity, clarify definitions, align ownership, prioritize issues, and drive decisions. Translate between business requirements and technical data concepts to ensure data standards, definitions, quality rules, and controls are practical, understood, and implementable. Influence stakeholders and advocate for disciplined data management practices. Use your skills to make an impact Required Qualifications. Bachelor's degree . years of experience in data management, data governance, data quality, business analysis, analytics . years in or supporting data governance, data stewardship, data quality, metadata management, or related data management programs. Experience defining, maintaining, or using business metadata, data dictionaries, data catalogs, business glossaries, critical data elements, lineage, reference data, or data quality rules. Working knowledge of data governance concepts, including data ownership, stewardship, metadata management, data quality, data classification, access and use controls, policy adherence, and issue management . years managing complex data issues, assess business impact, support root-cause analysis, recommend solutions, and collaborate across multiple teams and business areas. Demonstrated commitment to improving data quality, usability, and responsible data use across the enterprise. Preferred Qualifications 5 years of experience in data management, data quality, business analysis, analytics, governance, or a related discipline in the healthcare industry. Experience with healthcare data domains such as member, provider, claims, clinical, financial, operational, product, regulatory, or customer data. Familiarity with healthcare privacy, security, regulatory, and compliance expectations, including HIPAA or other applicable healthcare data handling requirements. Experience with data governance tools, data catalog platforms, data quality tools, metadata management tools, workflow systems, or issue management platforms. Familiarity with tools such as Collibra, Informatica, Alation, Microsoft Purview, Atlan, ServiceNow, Jira, or similar platforms. Familiarity with SQL, data profiling, BI/reporting tools, cloud data platforms, data warehouses, data lakes, master data, reference data, or data lineage concepts. Experience supporting governance for reporting, analytics, data products, digital transformation, automation, or AI-enabled initiatives. Certifications such as Certified Data Management Professional — DAMA CDMP, Data Governance and Stewardship Professional, Applied Data Governance Practitioner, or equivalent data governance/data management certification.