Data Modeler​/Data Architect

Job Description

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

• Location:
  
  Remote, NY
• Duration: 3 Months (Possible Extension)

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.

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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.

• 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