• Design and develop new ETL and Business Intelligence Solutions • Monitor and enhance production jobs and legacy ETL processes • Collaborate with existing team for database design and maintenance • Troubleshoot and resolve technical issues while ensuring data security

• Design, develop, and maintain Databricks ETL/ELT pipelines to process Medicaid claims, eligibility, encounters, provider files, and supplemental datasets • Ingest data from MMIS systems, state data warehouses, managed care organizations, and other Medicaid program data sources • Implement transformation, validation, and enrichment logic aligned to Medicaid data quality standards • Optimize Spark jobs for performance and cost efficiency across large Medicaid datasets • Build and maintain Data Lake models for auditability, lineage, and compliance • Develop Power BI semantic models, dashboards, and reports that support Medicaid operations • Collaborate with Medicaid program staff, policy teams, actuaries, and data governance groups

• Partner with business stakeholders to translate domain knowledge into structured analytical and semantic representations. • Design, develop, and maintain enterprise semantic models. • Collaborate with data engineers to shape silver and gold datasets. • Build AI-ready data products by enriching datasets with business definitions and hierarchies. • Develop and optimize Power BI semantic models. • Create and manage standardized KPIs and calculations using DAX. • Document business logic, data definitions, and metric context. • Implement data governance controls. • Publish trusted semantic models and datasets. • Monitor and optimize model performance.

• Deliver client-specific analytics solutions: Use Ursa Studio to develop, implement, and maintain Synthetic Objects, Data Marts, and measures tailored to client needs that enable rapid insight and drive operational and clinical impact. • Partner with Customer Success: Collaborate with Technical Customer Success Managers and leadership to scope, plan, manage, and support analytics engineering workstreams with clients, including multi-month embedded engagements and ad hoc initiatives. • Consult and train clients: Provide hands-off-keyboard expertise in analytics engineering using Ursa Studio, including technical scoping, advisory consulting, and training on best-practice analytics workflows using Ursa’s platform. • Effectively balance being responsive to client requests with building better solutions based on our experience and expertise. • Contribute to Ursa product/cross-client solutions: Build scalable, high-impact data models and analytics components that enhance Ursa's SaaS platform and marketplace, making powerful analytic tools accessible to all clients. • Thoughtfully work with AI-assisted tooling: Leverage AI tools (including internally developed Ursa Compass) and capabilities to accelerate and improve our delivery approach, appropriately apply the domain knowledge and human intelligence to ensure sound output. • Ensure high-quality written and verbal communication: Clearly document solution approaches and final deliverables for both technical and non-technical stakeholders. • Maintain standards and security: Stay current with healthcare data regulations and Ursa’s privacy and security policies, including HIPAA compliance.