Data Architect

Current-State & Functional Data Mapping

• Participate in functional discovery sessions with Domain SME to understand data needs across patient access, enrollment, PA/ePA, BV, case management, and hub operations.
  Map current data entities, data flows, and integration touchpoints based on functional and workflow requirements, not reverseengineering.
  Identify data duplication, ownership gaps, inconsistencies, and pain points that affect patient journeys and case workflows.
  Produce data capability maps, data domain definitions, and functional-to-data traceability.

Industry Standards & FutureState Alignment

• Align data requirements with industry standards such as NCPDP, X12/834/270/271, FHIR (if applicable), and hubservices data exchange conventions.
  Identify gaps between current data handling and modernized expectations (availability, quality, interoperability, security).
  Recommend patterns for patient record unification, eligibility/benefits data, case management data, and PA/ePA data.

Target-State Data Architecture

• Define future-state data domain models supporting patient access, enrollment, case management, and hub workflows.
  Design the canonical data model, event schemas, and data exchange patterns for the target platform.
  Define boundaries for analytical vs. operational data, including caching, eventing, and realtime data needs.
  Contribute to service/domain decomposition with architects by providing datadriven boundaries.
  Recommend the right platform components:
  Cloud data stores (RDS, Cosmos, DynamoDB, PostgreSQL, etc.)
  Event streaming (Kafka)
  Operational data stores (ODS)
  Master data management (MDM) considerations
  Data lake/lakehouse considerations (if future analytics are in scope)

Data Governance & Quality

• Define minimal viable governance needed for the modernized AMP platform (taxonomy, lineage, stewardship, quality rules).
  Recommend privacy/security guardrails (HIPAA, PHI/PII handling, masking, access controls).
  Propose reference patterns for structured logging, observability, traceability, and auditability.

Required Experience

• 10+ years in data architecture, data engineering, or enterprise architecture roles.
  Handson experience designing operational data models for healthcare, patient access, specialty pharmacy, or hubservice workflows (preferred).

Strong knowledge of:
Relational and NoSQL database design
Event-driven data patterns (Kafka, Kinesis)
APIled data integration
Healthcare data exchange formats (NCPDP, X12 270/271/834, prior auth workflows)
Experience defining canonical data models and domaindriven data boundaries.
Strong understanding of HIPAA compliance, PHI protection, audit requirements, and data governance.
Ability to convert functional/process insights into robust data structures.
Experience working in cloud platforms (AWS, Azure) with modern data services.