Business Analyst - CMS ONC Interoperability

Job Description:

Title: Business Analyst
Location: 100% Remote
Job Duration: 03-06 months (Contract + High chances of extension)
Pay rate: $65-$72/hr. on W2

Job Description:
100% Remote but prefer local candidates (Pittsburgh) who would be able to work onsite 2-3 days a week
Must complete the Sr BA - Interoperability Assessment in Glider
Business Analyst CMS ONC Interoperability

Job Summary
The Business Analyst will play a critical role in enabling end to end interoperability solutions within the CMS ONC ecosystem. This position requires strong technical fluency across modern data engineering patterns, API-driven interoperability, and ELT/ETL workflows. The ideal candidate will support complex data pipelines, SmileCDR operations, and FHIR-based data exchange while partnering closely with engineering, architecture, compliance, and external customers.
This role bridges business needs with technical execution translating requirements into data mappings, validating data flows, and supporting scalable, high reliability data integrations across clinical and administrative systems.

Key Responsibilities

Data Pipelines & Integration Support
Manage and support all ELT processes, ensuring data quality, reliability, and on time delivery across diverse source systems.
Troubleshoot data pipeline failures, data quality exceptions, and ingestion issues across cloud and on prem environments.
Oversee SmileCDR operations including configuration, deployment coordination, debugging, and monitoring to meet CMS ONC mandates.
FHIR / HL7 Interoperability
Perform detailed mapping of source data to FHIR R4 resources, profiles, and implementation guides (PDex, Patient Access API, Provider Access API, etc.).
Validate FHIR transactions and APIs via tools like Postman, SmileCDR, and custom validation frameworks.
Technical Business Analysis & Requirements Partner with architects and engineers to translate business requirements into actionable data specifications, API requirements, and process workflows.
Perform detailed impact assessments, system analysis, and data lineage documentation.
Testing & Quality Assurance
Conduct end to end validation of ELT pipelines, FHIR resources, API payloads, and cross-system data reconciliation.
Support automated and manual testing for data accuracy, schema changes, and interoperability compliance.
Customer & Stakeholder Engagement
Collaborate with internal and external customers to gather requirements, define acceptance criteria, and guide solution design.
Communicate complex data and interoperability concepts to both technical and non technical audiences.
Documentation & Governance
Develop comprehensive documentation including data dictionaries, mapping documents, business rules, SOPs, and interoperability artifacts.
Contribute to data governance, quality, and metadata initiatives aligned with CMS interoperability requirements.

Qualifications Required

Education: Bachelor s degree in computer science, Information Systems, Data Management, or related field; Master s preferred.
Experience: 5+ years as a Business Analyst with strong exposure to data engineering, APIs, interoperability, or healthcare data systems.

Technical Skills:

Strong knowledge of ELT processes, SQL, JSON, APIs, and data validation techniques.
Hands on understanding of FHIR R4, HL7, and healthcare data (claims, clinical, member, provider, etc.).
Experience with data mapping, transformation logic, and source to target specifications.
Soft Skills: Excellent communication, structured problem solving, stakeholder engagement, documentation, and cross functional collaboration.
Preferred Qualifications (Updated as requested)
Hands on experience with SmileCDR, HAPI FHIR, or other interoperability platforms.
Certifications in business analysis, data engineering, cloud data platforms, or interoperability standards.
Industry knowledge of CMS ONC Interoperability, Patient Access API, PDex, NDH, and payer-to-payer exchange requirements.
Experience with Confluent (Managed Connectors/Kafka), Apache Flink, or similar streaming frameworks.
Exposure to Monte Carlo Data Observability or similar data quality/lineage/monitoring platforms.
Familiarity with modern data lakehouse and query engines such as Apache Iceberg and Starburst.
Experience with dbt (data build tool) for modeling, transformations, lineage, and analytics engineering workflows.