Senior Healthcare Data Modeler

We are looking for a highly technical and hands-on Senior Healthcare Data Modeler to lead a global data modeling team responsible for designing, implementing, and documenting data model solutions which are a core component of the SaaS platform. The role requires a deep understanding of healthcare data domains (Claims, Membership, Provider, Billing, Interoperability, Clinical, etc.) and expertise in NoSql data modeling. 

The Senior Healthcare Data Modeler will work closely with the Director of Data Modeling to define modeling standards and metadata governance and ensure that data model solutions enable our internal teams and customers to nimbly build comprehensive data products that optimally structure and organize data to meet analytic and operational use cases. 

Your deep experience in identifying key business needs, defining and governing data model design standards, and employing data architecture strategies that align with business and technical needs will be key to the success of our highly differentiated, automated, and scalable data platform capabilities. 

All of this coupled with your passion for improving outcomes for all healthcare stakeholders will drive our company success. This represents a great opportunity to blaze your own trail working in a start-up organization in a cross-functional, talented team to move the needle on some of the most pressing challenges in healthcare. 

You Will: 

• Lead a global team of data modelers to build scalable, high-performance conceptual, logical and physical data models aligned with enterprise architecture and industry standards.  
  

• Define and enforce data modeling best practices, including schema evolution, lossless data modeling, metadata management, and data versioning.  
  

• Convert conceptual and logical data models into optimized physical ERDs using enterprise data modeling tools (Erwin, ER/Studio, DBT, or similar).  
  

• Ensure models support analytical (data science, actuarial, reporting) and operational (Claims, Care Management) use cases.  
  

• Maintain metadata, business glossary, and data dictionaries to support data lineage and governance.  
  

• Own data modeling workflows, including version control, schema deployment, and upgrade automation.  
  

• Work with engineering teams to implement data models in Databricks, Snowflake, and modern cloud architectures.  
  

• Optimize data models for update performance, query performance, indexing, partitioning, and storage efficiency as appropriate.  
  

• Ensure data enrichment (standardization, transformations, algorithms, and grouping) is seamlessly integrated into the data models.  
  

• Collaborate with Director of Data Modeling and client implementation teams to understand client needs, assess data model impact, and enhance models for efficient implementations.  
  

 
What We're Looking For: 

• 8+ years of experience in data modeling, enterprise data architecture, and cloud-based data engineering 
  

• 4+ years leading data modeling teams in enterprise environments.  
  

• Expertise in enterprise data modeling tools (Erwin, ER/Studio, DBSchema, or similar).  
  

• Strong hands-on experience with cloud data platforms (Databricks, Snowflake) and data lakehouse architectures.  
  

• Deep understanding of healthcare data models across Core Payer (Claims, Membership, Enrollment, Provider, Billing, Premium) and Clinical Interoperability (FHIR, HL7, ADT, CCDA, etc.) domains.  
  

• Experience with NoSql modeling, schema evolution, lossless data modeling, and data versioning strategies.  
  

• Strong background in SQL, performance tuning, and query optimization for large-scale datasets.  
  

• Hands-on experience with data engineering workflows, including data pipeline integration, ELT/ETL optimizations, and data transformation frameworks.  
  

• Ability to mentor junior modelers, enforce modeling best practices, and drive adoption of enterprise data standards.  
  

• Excellent collaboration skills to work with data architects, engineers, analysts, and client implementation teams.  
  

Nice to Have: 

• Healthcare reporting experience. 
  

• Experience with OBT, data lakehouse, and metadata management frameworks.  
  

• Familiarity with business intelligence (BI) and reporting solutions on modern cloud data warehouses.  
  

• Knowledge of APIs, SDKs, and data distribution frameworks for enabling real-time and batch data access.  
  

• Experience with data governance, security, and regulatory compliance in healthcare data management.