End-to-end Data Modeling: Lead the full modeling lifecycle (Conceptual, Logical, and Physical), ensuring healthcare business rules are accurately translated into the database.
Hybrid Architecture: Dimensional modeling (Star Schema) for consumption and analytics layers.
Standardization and Governance: Define and propagate naming conventions, entity standards, keys, and metadata to ensure consistency across squads.
Layer Design (Medallion Architecture): Develop the logical design of datasets and organize data layers (Bronze, Silver, Gold).
Documentation and Lineage: Ensure end-to-end data lineage and maintain technical documentation to enable self-service BI for other teams.
Model QA: Serve as a technical reviewer of models created by engineers and analysts, ensuring performance and data integrity.

Strong experience in relational and non-relational modeling.
Advanced proficiency with modeling tools (e.g., ERwin, PowerDesigner, SQLDBM, or dbdiagram.io).
Deep knowledge of Data Vault and experience developing architectures using Data Vault for the integration (Raw/Storage) layer, including Vault 2.0, and familiarity with Kimball and Inmon methodologies.
Experience with cloud data warehouses (e.g., Snowflake, BigQuery, or Databricks).
Fluency in SQL for validating and auditing physical models.
Plus: Knowledge of healthcare data standards (such as HL7 or FHIR).

Mid-level Data Architect

Key skills