Senior Healthcare Data Modeler EDW / Cloud Modernization

Job Description Job Description Senior Healthcare Data Modeler - EDW / Cloud Modernization Location: Remote, Continental U.S.
Preferred Location: Central U.S. / Midwest
Travel: Occasional Mot open to third parties Position Summary We are seeking a hands-on Senior Healthcare Data Modeler to support a large Enterprise Data Warehouse and cloud modernization initiative. This role will work with complex healthcare datasets and translate business requirements into scalable enterprise data models and solutions.
The Senior Healthcare Data Modeler will own the design, governance, and evolution of conceptual, logical, and physical data models supporting the EDW and its modernization. The environment is transitioning from a legacy Teradata EDW toward modern Azure and Snowflake cloud architecture. The ideal candidate brings deep healthcare data modeling experience, expert SQL skills, strong data governance and metadata knowledge, and hands-on experience designing enterprise data models across Medicaid, Medicare, claims, provider, TPL, and member data. Responsibilities Data Architecture & Strategy

• Develop long-term data architecture strategies, standards, and roadmaps in collaboration with business and technical stakeholders.
• Lead data architecture, data modeling, and data movement initiatives supporting Medicaid, Medicare, and Commercial healthcare data.
• Work across healthcare subject areas including claims, provider, TPL, and member data.
• Define how logical designs translate into physical databases and how data flows through successive architectural layers.
• Maintain accurate documentation of the enterprise data architecture and environment.

Data Modeling & Design

• Translate complex business requirements into scalable enterprise data models.
• Design and maintain conceptual, logical, and physical data models across staging, integration, and semantic/presentation layers.
• Develop dimensional models using Kimball star/snowflake, normalized OLTP/3NF, OLAP, and Data Vault modeling techniques.
• Implement Slowly Changing Dimensions, role-playing dimensions, dimensional hierarchies, surrogate keys, and data classifications.
• Define primary and foreign keys, indexes, partitioning, constraints, and referential integrity rules.
• Create and maintain ERDs, data flow diagrams, and data model documentation using Erwin or comparable modeling tools.

Data Governance, Quality & Compliance

• Ensure data architecture and modeling practices align with healthcare regulatory and security requirements.
• Oversee source-to-target mapping, data movement, interfaces, and data quality.
• Maintain data dictionaries, business glossaries, metadata, lineage documentation, and data modeling standards.
• Support classification and protection of PII and PHI in accordance with applicable healthcare data security requirements.
• Support Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, MDM, Data Archival, and Data Migration initiatives.

Collaboration & Delivery

• Partner with Data Architects, ETL/Data Engineers, Business SMEs, BI Developers, and DBAs throughout the architecture and implementation lifecycle.
• Provide technical recommendations for scalable data warehouse, data mart, data mining, and analytics solutions.
• Address data challenges involving systems integration, compatibility, and multi-platform environments.
• Develop testing criteria to ensure the fidelity and performance of data architecture.
• Communicate risks and issues clearly to project and stakeholder teams.

Cloud Modernization & Migration

• Support modernization of legacy Teradata data models to Azure and Snowflake.
• Contribute to target-state architectures involving Azure Synapse, Databricks Lakehouse, and Snowflake.
• Design models supporting Medallion architecture, including Bronze, Silver, and Gold layers.
• Work with Delta Lake and Parquet patterns.
• Assess existing data models for modernization, redundancy, performance, and optimization opportunities.

Required Qualifications

• BS or MS in Computer Science, Business Information Systems, Engineering, or a related field.
• 10+ years of IT experience.
• 7+ years of data modeling, data strategy, and roadmap experience supporting large, complex healthcare environments.
• Experience implementing large-scale, end-to-end Data Management and Analytics solutions.
• 5+ years of healthcare data modeling experience involving Medicaid, Medicare, and/or Commercial healthcare data.
• 5+ years of experience with Erwin or comparable data modeling tools such as ER/Studio or SQL Developer Data Modeler.
• Expertise in conceptual, logical, and physical data modeling.
• Expertise with normalized OLTP, OLAP, MDM, and dimensional modeling techniques.
• Strong experience with star schemas, Slowly Changing Dimensions, role-playing dimensions, dimensional hierarchies, and data classification.
• 5+ years of expert-level SQL experience, including complex analytic queries, stored procedures, DDL, DML, DCL, query optimization, and ANSI SQL.
• 5+ years of experience with Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, MDM, Data Archival, and Data Migration.
• Strong knowledge of HIPAA, PHI, PII, and healthcare data security requirements.
• Strong problem-solving, communication, influencing, and presentation skills.
• Ability to work independently in a fast-paced environment with multiple concurrent priorities.

Preferred Qualifications

• State Medicaid EDW or MMIS experience.
• Experience with Medicaid federal reporting programs such as T-MSIS, PERM, MARS, or Quality of Care.
• Teradata Vantage experience and exposure to modernization of Teradata workloads to cloud platforms.
• Microsoft Azure experience, including Azure Data Lake Storage, Azure Data Factory, and Purview.
• Azure Synapse and/or Databricks Lakehouse experience.
• Snowflake experience, including data object design and performance tuning.
• Experience with Delta Lake, Lakehouse architecture, or Microsoft Fabric.
• Experience with Data Vault modeling.
• Power BI or Tableau experience.
• Hands-on ETL experience with Informatica, Azure Data Factory, or similar tools.
• Python or R experience.
• Exposure to AI/ML or GenAI tools used for data modeling, documentation, or metadata enrichment.

Work Arrangement

• 100% remote within the Continental U.S.
• Central U.S. / Midwest candidates preferred.
• Occasional travel may be required.
• This role works across distributed and matrixed business and technology teams.