The ideal Data Architect candidate will have deep expertise in the healthcare payer domain, with strong knowledge of interoperability standards (FHIR, HL7, USCDI-US Core) and cloud-native data architecture. Hands-on proficiency in Databricks, Azure, and data modeling (especially dimensional modeling) is essential. The candidate should be able to work independently, collaborate effectively with business teams and senior data architects, and develop scalable solutions.
Working mode: This role follows a hybrid model, requiring 3 days onsite in the Philadelphia (PHL) area.
Skill Grid:
Mandatory (must-have) skills are highlighted in yellow. The others are related areas and considered good-to-have tool skills.
Skill Area
JD Requirement
Details
Core Experience
Data Architecture
10+ years, preferably in healthcare; end-to-end data processing.
Healthcare Domain
Healthcare data expertise
Payor ( strong expertise is needed), Clinical, Claims, Member, Provider, EHR data models
Interoperability Standards
FHIR, HL7, USCDI-US Core
Experience with HEDIS, CMS interoperability, CCDs, HIE
Cloud Platforms
Azure, AWS, Google Cloud Platform, Databricks, Snowflake
5+ years designing/solutioning cloud data platforms. Hands on Azure and Databricks are mandatory
Data Modeling
Dimensional modeling
Tools like Erwin; healthcare-specific requirements
Leadership & Collaboration
Independent thought leader
Ability to self-direct, collaborate with analysts, scientists, IT, business leaders and develop solutions.
Databases
SQL & NoSQL
Proficiency in SQL, NoSQL, PySpark, Python
Integration Tools
ADF, Databricks, Kafka, Informatica, IBM DataStage
Hands-on experience with modern ETL/ELT tools
Governance & Compliance
HIPAA, GDPR, Data Governance
Policies for integrity, quality, security, compliance
BI & Analytics
BI platforms
Understanding of BI/analytics platforms
Preferred Qualifications
Healthcare systems & large-scale data
5+ years managing large-scale healthcare data systems; Epic/Cerner experience is a plus