$ cat jobs/staff-software-engineer-data-extraction-pivotal-health-2354a13e38e6.json
Staff Software Engineer, Data Extraction
ABOUT PIVOTAL HEALTH Pivotal Health is the leading technology platform that helps healthcare providers get paid fairly in an increasingly complex reimbursement landscape. Today, many providers face persistent underpayment from health insurance companies, despite delivering high-quality care. While processes like IDR (Independent Dispute Resolution) were designed to promote fairness, they’re often administrative-heavy, time-consuming, and difficult to navigate without the right tools. Pivotal Health combines software, data, and service into a seamlessly integrated, AI-driven platform that simplifies these complex reimbursement workflows. We help providers efficiently dispute underpaid claims, reduce administrative burden, and recover the reimbursement they’re entitled to; without adding more work to already stretched teams. Our full-service IDR solution is just the starting point. We’re building solutions that enable providers to operate with clarity, control, and confidence across the reimbursement journey. ABOUT THE ROLE Pivotal Health is expanding its investment in clinical data infrastructure as a core strategic initiative. We are building a state-of-the-art clinical data platform that collects, processes, and transforms complex healthcare information from a variety of sources and formats into structured, high-quality data assets. This platform serves as the foundation for a growing set of products, analytics capabilities, and operational workflows across the organization. As healthcare data continues to grow in volume and complexity, building systems that securely process, govern, and deliver high-quality clinical data has become a critical capability. This engineer will own key systems within that platform, helping define how clinical data is ingested, processed, normalized, and delivered at scale. As a Staff Software Engineer focused on Data Extraction, you will design and build the ingestion, parsing, normalization, and enrichment pipelines that turn messy he