Developer (Data Modeler / Architect)

Job Title: Developer (Data Modeler / Architect)
Job Location: New York, NY
Job Duration: 6 Months (possibility of extension)
Payrate: $30.00 - $50/ hr. on w2

Job Summary:

• The Data Modeler / Architect, with expertise in the healthcare domain, is responsible for designing, implementing, and governing enterprise data models and data architecture that support data warehouses, data marts, analytics, reporting, and AI/ML initiatives.
• This role defines and enforces modeling standards and best practices to ensure high data quality, scalability, reusability, and minimal data redundancy, while enabling efficient data movement across Provider, Payer, and Clinical domains in cloud-native healthcare data platforms.

Key Responsibilities:

• Work with the team to design and implement data strategies (Data Mesh/Lakehouse), build data flows and develop conceptual, logical and physical data models.
• Develop strategies to simplify data movement across disparate domains (Provider, Payer, Clinical), reducing technical debt and redundant pipelines.
• Create and maintain conceptual, logical, and physical data models, along with corresponding metadata, according to enterprise standards using the Erwin tool.
• Dimensional Modeling Design: Design and develop efficient dimensional models (star schema, snowflake schema) for large-scale data warehouses, ensuring that data structures support analytical and reporting requirements.
• Understand and translate business needs into data models to satisfy enterprise analytics & reporting and AI/ML needs with hands-on expertise multi-model data architecture expertise across relational, unstructured, and vector databases, including healthcare data such as audio transcripts, video, waveforms (ECG/EEG), and medical imaging (DICOM and non-DICOM).
• Cloud-Native Data Platform Design for AI/ML, Design and architect cloud-based data platforms on AWS/Azure leveraging Snowflake Iceberg tables to store and manage structured and unstructured data, enabling scalable feature engineering, model training, and inference workloads for AI/ML initiatives.
• Collaborate with data scientists and ML engineers to ensure high-quality, accessible, and well-structured data for machine learning use cases.
• Lead the mapping of source data into FHIR (for exchange) and OMOP (for research/analytics), ensuring strict adherence to LOINC, SNOMED, and ICD-10 coding schemes.
• Establish data architecture standards, best practices, naming conventions, and documentation.
• Design, build, and maintain robust data pipelines using Snowflake-native features (such as Dynamic tables, Streams, and Tasks), while developing and optimizing SQL, stored procedures, and scripts for data ingestion, and transformation.
• Strong Data Analysis, SQL Querying, Data Profiling & Healthcare Domain Knowledge: Leverage advanced data analysis techniques, SQL querying, and data profiling to identify trends, patterns, and data anomalies.
• Perform reverse engineering of physical data models from databases and SQL scripts.
• Implement data quality, governance, data contracts and security best practices while optimizing cost and performance.
• Develop architectural patterns that ensure Snowflake performance and manage Total Cost of Ownership (TCO) through credit optimization and warehouse right-sizing.

Experience Requirements:

• 7+ years in Data Architecture, Modeling, or Warehousing.
• Snowflake Expertise: 2+ years of deep, hands-on experience with Snowflake-native features.
• Minimum 3+ years’ experience in Healthcare Domain: In-depth knowledge of FHIR, HL7, X12, DICOM communications protocols for healthcare data exchange, and expertise with OMOP (i2b2 is a bonus) data models.