Data Modeler

Experience : 6 - 8 Years

Location : Pune / Bangalore / Gurugram / Noida

Role : Data Modeler

Job Summary :

We are looking for an experienced Data Modeler with strong expertise in healthcare payer data, enterprise data modeling, and modern Lakehouse architectures. The ideal candidate should have hands-on experience in designing foundational and dimensional data models, working with Databricks, SQL, and medallion architecture.

The candidate will be responsible for developing scalable, reusable data models across core healthcare payer domains, collaborating with data engineering, architecture, business, and governance teams to ensure data accuracy, consistency, and alignment with business requirements.

Key Responsibilities :

- Design and maintain foundational Gold-layer data models, including defining data grain, keys, historical tracking (SCD), and relationships for core healthcare payer entities (Member, Coverage/Eligibility, Claims, Provider).

- Design and develop Platinum-layer serving models, including dimensional facts, dimensions, business-specific views, and metric views.

- Define and implement reference data management and identity-resolution strategies.

- Partner with data engineering teams to establish transformation and data-loading patterns, ensuring model accuracy through reconciliation and validation.

- Leverage available AI accelerators for data models, mappings, and technical documentation.

- Collaborate with data architecture leads, business SMEs, and data governance teams.

- Support data modernization and migration initiatives, ensuring consistency between legacy EDWs and modern platforms.

Required Skills & Qualifications :

- 6 - 8 years of hands-on experience in conceptual, logical, and physical data modeling.

- Strong experience with normalized (3NF / Data Vault) and dimensional (Kimball) modeling techniques.

- Strong healthcare payer domain knowledge (Claims, Member, Enrollment, Eligibility, Provider, Benefits).

- Expert-level SQL skills for complex queries, data analysis, and validation.

- Hands-on experience with Databricks, Delta Lake, Lakehouse, and Medallion Architecture.

- Experience with SCD, reference data management, and identity resolution.

- Knowledge of data governance (metadata, lineage, business glossary, data quality).

- Understanding of PHI/PII data protection and HIPAA compliance.

Preferred Qualifications :

- Experience with legacy Oracle EDW and cloud-based Lakehouse modernization.

- Familiarity with AI-assisted data modeling and documentation accelerators.

- Strong stakeholder management and communication skills.