Data Modeler / Data Architect – Healthcare (Snowflake, Cloud, AI/ML) - 26-01713

Data Modeler / Data Architect – Healthcare (Snowflake, Cloud, AI/ML) Location: Remote, NY Duration: 3 Months (Possible Extension) Position Overview We are seeking an experienced Data Modeler / Data Architect with deep expertise in the healthcare domain to design, implement, and govern enterprise data models and cloud-native data architectures. This role will support data warehouses, data marts, analytics, reporting, and AI/ML initiatives across Provider, Payer, and Clinical domains. The ideal candidate will have strong hands-on Snowflake expertise, healthcare interoperability knowledge (FHIR, HL7, X12, DICOM), and experience designing scalable data platforms that support structured, unstructured, and vector data workloads. Key Responsibilities Enterprise Data Modeling & Architecture • Design and maintain conceptual, logical, and physical data models using Erwin • Define enterprise modeling standards, naming conventions, and governance practices • Perform reverse engineering of physical models from databases and SQL scripts • Develop strategies to reduce technical debt and redundant data pipelines • Establish data contracts and governance frameworks Dimensional Modeling & Data Warehousing • Design and implement dimensional models (Star Schema, Snowflake Schema) • Build scalable data warehouses and data marts for analytics and reporting • Optimize structures for performance, scalability, and minimal redundancy • Support enterprise analytics and AI/ML feature engineering Cloud-Native Data Platform & Snowflake Engineering • Architect cloud-based platforms on AWS/Azure • Leverage Snowflake-native features: • Dynamic Tables • Streams • Tasks • Iceberg Tables • Develop and optimize: • Advanced SQL • Stored procedures • Data ingestion and transformation pipelines • Implement cost optimization strategies (credit usage & warehouse right-sizing) • Ensure high-performance Snowflake architectural patterns Healthcare Data & Interoperability • Lead source data mapping into: • FHIR (exchange) • OMOP (research/analytics) • Ensure compliance with: • LOINC • SNOMED • ICD-10 • Work across healthcare data types including: • Clinical records • Claims data (X12) • HL7 interfaces • Medical imaging (DICOM & non-DICOM) • ECG/EEG waveforms • Audio & video clinical transcripts • Experience with i2b2 is a plus AI/ML Data Architecture • Design cloud-native AI/ML data platforms • Enable scalable feature engineering, model training, and inference • Collaborate with Data Scientists and ML Engineers • Support vector and multi-model database architectures Data Governance & Quality • Implement data profiling and advanced data analysis techniques • Ensure data quality, integrity, security, and compliance • Develop performance and cost governance frameworks • Maintain enterprise metadata standards Cross-Functional Collaboration • Analyze how data flows across systems and business domains • Identify system errors, deficiencies, and improvement opportunities • Coordinate testing, system patches, and upgrades • Create user documentation and training materials • Evaluate emerging technologies and provide implementation strategies Required Experience • 7+ years in Data Architecture, Data Modeling, or Data Warehousing • 3+ years in Healthcare Domain • FHIR • HL7 • X12 • DICOM • OMOP • 2+ years deep Snowflake hands-on experience • Strong SQL and data profiling expertise • Experience designing multi-model data architectures • Experience in AWS and/or Azure environments Preferred Experience • Experience with Data Mesh or Lakehouse architectures • Experience with i2b2 data models • Experience with vector databases and AI/ML workloads • Experience managing Total Cost of Ownership (TCO) in cloud environments Educational Requirements • Bachelor’s Degree in: • Computer Science • Systems Engineering • Applied Mathematics • Business Administration • Economics/Statistics • Telecommunications • Data Communications • Or related field OR • Equivalent combination of education, training, and progressive experience Minimum five (5) years of progressive experience in data processing, computer systems, and applications required. Core Competencies • Enterprise Data Architecture • Healthcare Data Standards & Interoperability • Snowflake Engineering & Optimization • Dimensional Modeling • Cloud Data Platforms (AWS/Azure) • AI/ML Data Enablement • Data Governance & Quality Management • Cross-Functional Collaboration