Data Modeler

Job Title: Data Modeler
Location: Atlanta, GA or Richmond, VA

Healthcare domain mandatory
 

Job Description
We are seeking a skilled Let's Data Modeler with strong experience in healthcare payer data environments to design, develop, and optimize enterprise data models that support analytics, reporting, and operational systems. The ideal candidate will have hands-on expertise in both normalized and dimensional data modeling techniques and a deep understanding of healthcare data structures, standards, and regulatory considerations.
Key Responsibilities
Design and maintain logical and physical data models for enterprise data platforms.
Develop normalized (3NF or equivalent) data models for transactional systems.
Create dimensional models (star/snowflake schemas) to support BI, analytics, and reporting needs.
Collaborate with business stakeholders, architects, and engineering teams to translate requirements into scalable data designs.
Ensure data models align with healthcare payer domain standards such as claims, membership, provider, eligibility, and benefits data.
Perform data analysis, profiling, and mapping between source and target systems.
Support data governance, metadata management, and data quality initiatives.
Optimize models for performance, scalability, and maintainability.
Participate in architecture reviews, data strategy discussions, and solution design sessions.
Required Skills & Qualifications
Direct experience working with healthcare payer data and analytics use cases.
Strong expertise in data modeling tools such as ERwin, ER/Studio, or similar.
Proven experience designing both normalized and dimensional data models.
Solid understanding of SQL, data warehousing concepts, and ETL processes.
Experience with enterprise data platforms (Snowflake, Redshift, Azure Synapse, BigQuery, etc.).
Knowledge of data governance, lineage, and metadata management concepts.
Strong analytical, problem-solving, and documentation skills.
Ability to work in cross-functional teams in Agile or hybrid delivery environments.
Preferred Qualifications
Experience working in large enterprise or consulting environments.
Familiarity with HIPAA compliance and healthcare data privacy standards.
Exposure to cloud data architectures (AWS, Azure, or GCP).
Experience supporting data lake/lakehouse architectures.