Data Modeler

EVERSANA

About The Position

We are seeking an experienced Data Modeler with strong expertise in the US Healthcare domain to design, develop, and optimize enterprise data models. The ideal candidate will analyze business requirements, translate them into scalable data architectures, and ensure consistency, quality, and performance across systems.

Requirements

Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, or related field.
6+ years of experience in data modeling and data architecture.
Extensive hands-on experience in the US Healthcare domain (Claims, Providers, Members, EHR/EMR, Payers, HIPAA compliance).
Strong expertise in: Conceptual, Logical, and Physical Data Modeling Dimensional Modeling (Star/Snowflake Schema) Data Warehousing Concepts Metadata Management
Strong SQL knowledge and experience with relational databases (e.g., SQL Server, PostgreSQL).
Experience working in Agile/Scrum environments.
Strong understanding of data governance, data quality, and master data management.
Strong analytical and problem-solving skills
Excellent stakeholder communication skills
High attention to detail and data accuracy
Ability to work independently and in cross-functional teams
Strong documentation and governance mindset

Nice To Haves

Experience working with healthcare standards such as: HL7 HIPAA FHIR
Exposure to cloud data platforms (Azure, AWS, GCP).
Knowledge of healthcare data models (Claims, Eligibility, Encounters, Clinical data).

Responsibilities

Analyze and translate complex business requirements into long-term, scalable data models.
Design and develop conceptual, logical, and physical data models aligned with enterprise architecture.
Work closely with business stakeholders, data architects, and development teams to define data flows and system integrations.
Evaluate and assess existing data systems for gaps, redundancies, and optimization opportunities.
Implement enterprise data strategies supporting analytics, reporting, and operational systems.
Develop and enforce data modeling standards and best practices to ensure coding consistency and governance compliance.
Review modifications to existing systems to ensure cross-platform compatibility and data integrity.
Update and optimize local data models and metadata repositories.
Conduct variance and discrepancy analysis to identify performance or data quality issues.
Troubleshoot, tune, and optimize data systems for performance, scalability, and reliability.
Support regulatory compliance requirements specific to US Healthcare (e.g., claims, EHR, HIPAA data handling standards).
Collaborate with ETL, BI, and application teams to ensure seamless data integration.