Data Engineer

About Waymark

Waymark is a mission-driven team of healthcare providers, technologists, and builders working to transform care for people with Medicaid benefits. Our community-based care teams—powered by proprietary data science and ML technologies—support care for tens of thousands of Medicaid members across multiple states, driving measurable reductions in avoidable emergency department visits and hospitalizations. We’re designing tools and systems that bring care directly to those who need it most—removing barriers and reimagining what’s possible in Medicaid healthcare delivery and we are seeking a highly experienced Data Engineer to join this mission.

This is a senior to principal-level individual contributor role who combines deep backend engineering fundamentals with specialized expertise in Electronic Health Record (EHR) data integration. You will report to data engineering leadership and setting the technical direction for our clinical data platform by leading the design, development, and optimization of data pipelines that ingest, normalize, and transform clinical data from diverse EHR and payer systems. 

If this resonates with you, we invite you to bring your creativity, energy, and curiosity to Waymark.

Key Responsibilities

EHR & Partner Integrations

• Architect production-grade data pipelines that integrate clinical data through multiple channels—direct EHR connections (e.g., Epic, Cerner, Athenahealth), health information exchanges (HIEs), health alliance networks, and third-party integration vendors—via FHIR R4 APIs, HL7v2 feeds, CCDA documents, and bulk data exports, while enforcing healthcare standards and clinical terminologies (ICD-10, SNOMED CT, LOINC, RxNorm), targeting sub-hour latency from clinical event to actionable insight and ≥99.9% pipeline reliability
• Lead end-to-end integration efforts with health plan partners, HIEs, health alliance networks, provider organizations, and data integration vendors—owning partner technical evaluation, connectivity, data mapping, validation, and production rollout

Data Platform & Tooling

• Build and optimize cloud-native data infrastructure (AWS) and ETL/ELT workflows using modern orchestration tools (e.g., Step Functions, dbt) with robust data quality monitoring and lineage tracking
• Develop reusable backend frameworks, libraries, and internal tooling that accelerate onboarding of new data sources—whether direct EHR feeds, HIE connections, or vendor integrations—with the goal of reducing new-partner integration time by 50% or more while improving developer productivity and reducing operational toil across engineering

ML/AI Enablement & Product Collaboration