Data Health Partner

Arcadia is dedicated to happier, healthier days for all. We believe that there is a better healthcare world – one powered by data. Our platform transforms complex, diverse data into a unified foundation for health, helping organizations deliver better care, boost revenue, and lower costs. We’re a team of fiercely driven individuals committed to making healthcare more sustainable—and we’re looking for passionate people to help us get there. For more information, visit arcadia.io. Why This Role Is Important to Arcadia Love data and want to make a difference? The Data Health Partner (DHP) plays a critical role in ensuring that customer data within Arcadia’s platform is accurate, reliable, and actionable. This role sits at the intersection of data validation, dataset analysis, backend troubleshooting, and cross-functional delivery. The Data Health Partner analyzes healthcare datasets, validates system behavior, and resolves data issues so customers can confidently trust and act on their data. The Data Health Partner operates within a matrix team structure alongside a TechOps Delivery Lead, Data Engineers, fellow DHPs, and the Customer Management team. In this environment, the role is expected to deliver technical work on planned timelines, identify risks early, and communicate proactively with cross-functional partners and leadership. While primarily focused on backend systems and data integrity, the Data Health Partner will often engage directly with customers to explain findings and support resolution efforts. The Data Health Partner is part of Arcadia’s TechOps organization and reports to the Data Health Manager, ensuring strong technical mentorship, structured growth, and alignment with data quality and platform best practices. Arcadia embraces modern tooling and innovation. The Data Health Partner is expected to thoughtfully leverage AI tools in daily work to enhance analysis, improve documentation, and increase efficiency while maintaining strong technical judgment and data security standards. What Success Looks Like In 3 months - Learn Arcadia’s data model, ingestion processes, and orchestration framework - Develop familiarity with assigned customer datasets and business context - Begin analyzing datasets to support validation and issue investigation - Use AI tools to enhance productivity in analysis and documentation In 6 months·       - Take ownership of data quality and monitoring processes associated with customers - Troubleshoot routine validation and orchestration issues with minimal assistance - Deliver assigned work within expected timelines - Identify risks to delivery and communicate proactively - Support customer-facing communication when technical clarification is needed   In 12 months - Manage day-to-day data validation and troubleshooting for complex activities independently - Apply lessons learned to improve quality and consistency for the team - Have customer facing conversations independently on a regular basis - Develop subject matter expertise in healthcare data - Leverage AI tools strategically to scale impact while maintaining compliance