• Ensure accurate and compliant Medicare and Medicaid encounter submissions. • Use data analysis and process improvement techniques to increase submission acceptance rates and operational efficiency. • Work independently on routine to moderately complex issues and support departmental goals through process improvement. • Support encounter data integrity by managing claims and encounter data errors. • Identify issues, recommend solutions, and ensure compliance with Medicaid data submission requirements. • Manage and analyze large datasets related to Medicaid claims and encounter data to identify trends and patterns. • Maintain data quality control processes to ensure accuracy and completeness of data. • Collaborate with teams to design and implement data management solutions. • Conduct data validation and quality assurance activities to ensure data integrity. • Develop and maintain documentation of data management processes.

• Define and govern metadata (data definition & structure) across workflows, automation, and AI-driven processes to ensure consistent, controlled system behavior • Establish standards for system configuration design, reuse, and lifecycle management across Salesforce and integrated platforms • Lead end-to-end data conversion as a business function—not just a technical activity • Partner with regions to drive data assessment, profiling, cleansing, and enrichment • Own object mapping from legacy systems to Salesforce and downstream platforms, ensuring decisions support operational continuity, auditability, and reporting integrity—including ERP transformations such as legal entity simplification • Own the end-to-end governance of system configuration changes, including intake, prioritization, impact assessment, and release management • Ensure all changes are evaluated for cross-process impact, data integrity, and downstream effects before deployment • Establish full traceability of metadata changes, ensuring who changed what, when, and why is always visible • Enable audit-ready systems with strong controls supporting regulatory, financial, and operational compliance • Govern AI agents (e.g., Agentforce) to ensure their actions are predictable, explainable, and aligned with business rules • Monitor utilization, accuracy, and outcomes, continuously optimizing AI performance against defined KPIs and guardrails • Provide governance over data conversion activities, ensuring alignment between metadata structures, data models, and migration logic • Validate that configuration and data transformations are consistent, controlled, and scalable • Serve as the governance counterpart to IT and platform teams, ensuring all system design and configuration decisions align with enterprise standards, scalability, and long-term maintainability • Ensure consistency of configurations and behaviors across Salesforce, ERP, and integrated systems, preventing fragmentation and uncontrolled customization