IKS Health - FHIR Data Architect - Healthcare Domain

: Role & Responsibilities : Healthcare Data Architecture : - Design and evolve enterprise healthcare data architectures supporting clinical, revenue cycle, operational, and financial domains. - Design scalable logical and physical healthcare data models that support interoperability, analytics, and operational workloads. - Define enterprise data modeling standards, metadata management practices, and architectural best practices. - Partner with engineering and product teams to establish reusable architecture patterns for healthcare data platforms. HL7 FHIR Architecture & Implementation : - Lead enterprise implementation of HL7 FHIR (R4/R4B/R5) leveraging Implementation Guides (IGs), Profiles, Extensions, StructureDefinitions, and Terminology Services. - Design FHIR-native integration strategies and implement best practices for FHIR profiling, validation, conformance, and interoperability. - Design healthcare data harmonization strategies that standardize and normalize data from diverse healthcare sources into consistent, analytics-ready information models. - Develop interoperability and transformation strategies for healthcare data exchanged through HL7 v2, FHIR, EDI, APIs, and other industry-standard formats while maintaining semantic consistency and data quality. Data Platform & Pipeline Engineering : - Design, develop, and maintain scalable ETL/ELT pipelines for clinical, revenue cycle, financial, operational, and workflow-related healthcare data. - Develop ingestion and transformation pipelines for HL7 v2, FHIR APIs, EDI transactions, and file-based healthcare data sources. - Build and optimize enterprise data models within modern cloud data warehouses to support analytics, reporting, and AI/ML workloads. - Design and implement streaming and event-driven data pipelines for near real-time healthcare applications. - Develop robust orchestration frameworks that deliver reliable, monitored, and observable data workflows. Cloud Infrastructure & Architecture : - Architect secure, scalable, and resilient healthcare data platforms across leading cloud platforms (AWS, Azure, or Google Cloud). - Design cloud-native data architectures using modern data storage, processing, messaging, orchestration, and analytics services. - Implement Infrastructure as Code (Terraform or equivalent) and cloud architecture best practices. - Design scalable data lake and lakehouse architectures to support structured and semi-structured healthcare data. - Optimize cloud infrastructure for performance, scalability, security, reliability, and cost efficiency. Healthcare Data & Compliance : - Ensure healthcare data platforms comply with HIPAA, HITECH, and applicable healthcare privacy and security regulations. - Partner with clinical, security, and compliance teams to implement data governance, metadata management, lineage, cataloging, and access controls. - Apply healthcare terminology standards including SNOMED CT, LOINC, ICD-10, CPT, and RxNorm to support semantic interoperability and standardized clinical data. Data Quality, Observability & Leadership : - Define and implement enterprise data quality, validation, observability, and monitoring frameworks to ensure completeness, consistency, conformance, and integrity of healthcare data. - Build monitoring capabilities to proactively detect data anomalies, schema drift, pipeline failures, and operational issues. - Mentor architects and data engineering teams through architecture reviews, technical guidance, and engineering best practices. - Partner with Data Science, AI/ML, Product, and Engineering teams to deliver trusted, high-quality datasets supporting advanced analytics and intelligent applications. Preferred candidate profile : Professional Experience : - 12+ years of experience in enterprise data engineering and architecture, with significant experience in cloud-native healthcare platforms. - Proven experience designing scalable healthcare data architectures and enterprise data platforms. - Strong experience working with clinical, revenue cycle, financial, and operational healthcare data. FHIR Implementation Expertise : - Extensive hands-on experience implementing HL7 FHIR standards in enterprise production environments. - Strong knowledge of FHIR Implementation Guides, Profiles, Extensions, StructureDefinitions, Terminology Services, and interoperability best practices. - Demonstrated experience integrating and harmonizing healthcare data across HL7 v2, FHIR, EDI, APIs, and other healthcare data formats. - Experience working with FHIR-enabled healthcare platforms such as Google Cloud Healthcare API, Azure Health Data Services, AWS HealthLake, HAPI FHIR, Firely, Smile CDR, or equivalent technologies. Technical Proficiency : - Strong programming experience with Python and SQL . - Experience with modern cloud data warehouses such as BigQuery, Snowflake, Redshift, Synapse, or equivalent platforms. - Hands-on experience with ETL/ELT frameworks, dbt, and workflow orchestration tools such as Airflow, Prefect, Dagster, or equivalent. - Experience designing streaming data pipelines and event-driven architectures. - Experience with Infrastructure as Code using Terraform or equivalent technologies. Healthcare Domain Expertise : - Strong understanding of healthcare interoperability standards including HL7 v2, HL7 FHIR, C-CDA, X12, SMART on FHIR, ICD-10, SNOMED CT, LOINC, CPT, and related standards. - Experience integrating with enterprise EHR/EPM platforms such as Epic, Oracle Health (Cerner), NextGen, Athenahealth, ModMed, MEDITECH, Veradigm, eClinicalWorks, or similar healthcare systems.