Data Architect

Ontrac Solutions LLC.; Detroit (MI); Remote; USD 165,000 - 262,000; Full time

Job summary

OnTrac is seeking a data architect to own architecture and delivery for a healthcare data platform expansion, covering rebate reconciliation, referral capture, FHIR/HL7 interoperability, EDI processing, and clinical data exchange. The role requires hands-on design of scalable, metadata-driven ingestion patterns and close collaboration with client stakeholders and distributed teams.

The contractor will architect ingestion pipelines for X12 EDI and MTF, design FHIR-based patterns with incremental

Qualifications

• Must have healthcare data experience including PBM or payer data flows.
• Expertise with HL7 v2 (ADT, SIU) and FHIR data models and mappings.
• Strong background in X12 EDI parsing and transformation.
• Proven API design capabilities for data ingestion and integration.
• Experience with metadata-driven data ingestion architectures.

Responsibilities

• Architect ingestion pipelines for X12 EDI and MTF files using Azure Data Factory and Databricks.
• Design FHIR-based ingestion patterns with incremental sync, throttling, and retry handling.
• Define canonical data models for referral, clinical documents, and provider-administered drug data.
• Extend metadata-driven ingestion framework to support new payload types.
• Architect HL7 ADT/SIU linkage for 340B eligibility determination.
• Design clinical document storage, indexing, and retrieval (CCD/C-CDA).
• Establish trading partner onboarding and configuration patterns.
• Guide reporting and analytics data model design for BI consumption.
• Collaborate with client stakeholders and vendor teams on integration points.

Skills

Healthcare PBM domain

340B program knowledge

HIE connectivity

Patient matching & identity resolution

API design

Metadata-driven architecture

Data platform

Tools

Azure Data Factory

Databricks

Spark

HL7 v2 / FHIR knowledge

Job description

OVERVIEW

OnTrac is seeking a highly skilled and experienced Data Architect to join a contractor program supporting a healthcare / pharmacy benefit management (PBM) customer. The role owns architecture and technical delivery for a data platform expansion covering rebate reconciliation, referral capture, FHIR / HL7 interoperability, EDI transaction processing, and clinical data exchange. It is ideal for a hands‑on architect who designs scalable, metadata-driven ingestion patterns that support current and future healthcare and pharmacy data feeds. The successful candidate will work closely with client stakeholders and distributed delivery teams to ensure project success from initial definition through final delivery.

ENGAGEMENT

• Location: United States, fully remote

REQUIRED QUALIFICATIONS

• Azure Data Factory, Databricks, and Spark-based data engineering
• HL7 v2 (ADT, SIU) and FHIR, including resource modeling and terminology mapping
• X12 EDI parsing and transformation experience
• Strong API design background
• Data platform and metadata-driven architecture patterns

PREFERRED QUALIFICATIONS

• Healthcare payer / PBM or pharmacy rebate domain experience
• 340B program knowledge
• HIE connectivity (Carequality, CommonWell, Direct Secure Messaging)
• HCPCS / J-Code familiarity
• Patient matching and identity resolution experience

SCOPE AND DELIVERY EXPECTATIONS

The following covers the scope of work we anticipate the contractor supporting throughout the project. This scope is in line with our expectations of the project but is subject to change.

• Architect ingestion pipelines for X12 EDI (835, 837, 832, 810) and MTF files using Azure Data Factory and Databricks
• Design FHIR-based ingestion patterns (API and bundle) with incremental sync, throttling, and retry handling
• Define canonical data models for referral, clinical document, and provider-administered drug data
• Extend the existing metadata-driven ingestion framework to support new payload types without platform redesign
• Architect HL7 ADT / SIU linkage supporting 340B eligibility determination
• Design clinical document storage, indexing, and retrieval architecture (CCD / C-CDA)
• Establish trading partner onboarding and configuration patterns
• Guide reporting and analytics data model design (tables and views for BI consumption)
• Partner with client stakeholders and vendor teams on integration points

GROWTH EXPECTATIONS

Comfort using AI-assisted development tools (for example, GitHub Copilot or Claude Code) as force multipliers. Not required on day one; expected to develop.

COMPETENCIES

• Adaptability across ambiguous, evolving scope
• Clear cross-functional communication with the client and distributed delivery teams
• Ownership and prioritization across multiple concurrent workstreams