Note: Please ensure your resume includes a valid LinkedIn profile link. Applications without a LinkedIn profile will not be considered.
Key Responsibilities:
Design and build EDI transaction processing pipelines on Azure (Logic Apps, Azure Functions, Azure Integration Account, Service Bus, API Management) to replace existing Edifecs-based workflows.
Re-platform X12 mapping, validation, and transformation rules from Edifecs specs/maps into Azure-native schemas and custom code.
Own end-to-end development for core healthcare transaction sets: 834 (Enrollment), 278 (Authorization), 270/271 (Eligibility), 835 (Remittance Advice), and 837 (Claims - institutional/professional/dental).
Partner with QE to define test scenarios, synthetic EDI file generation, and automated validation for parity between legacy Edifecs output and new Azure pipelines.
Apply AI/GenAI tooling (Copilot-style code assistance, LLM-based test case or mapping-rule generation) to speed up migration and reduce manual mapping effort.
Troubleshoot transaction failures, envelope/segment errors, and companion-guide deviations across trading partners.
Document mapping specifications, migration runbooks, and cutover/rollback plans for each transaction set.
Collaborate with onshore/offshore teams, EDI business analysts, and clearinghouse/trading-partner contacts during parallel-run and go-live phases.
Required Skills & Experience
5+ years hands-on experience with X12 EDI transactions in a healthcare payer or clearinghouse environment (834, 278, 270/271, 835, 837 mandatory).
Working knowledge of Edifecs components (XEngine, Transaction Manager, SpecBuilder, or similar) and experience migrating off a legacy EDI platform.
Practical development experience on Azure integration services: Logic Apps, Azure Functions, API Management, Service Bus/Event Grid, Azure Integration Account (X12 schemas/agreements).
Proficiency in C#/.NET or Python for custom transformation and validation logic.
Familiarity with companion guides, HIPAA 5010 implementation guides, and trading-partner onboarding.
Must have exposure to AI-assisted development tools (GitHub Copilot or equivalent)
Experience with SQL and cloud data stores for transaction logging, reconciliation, and audit trails.
Strong troubleshooting skills for EDI envelope, segment, and business-rule level errors.
Preferred / Good to Have:
Prior experience on an Edifecs-to-cloud (Azure/AWS) modernization project.
Knowledge of Azure Health Data Services or FHIR.
Exposure to CI/CD pipelines (Azure DevOps) for integration deployments.