Job Summary :

We are looking for an experienced Senior Data Architect to support the modernization and enhancement of Enterprise Analytic Data Warehouse (ADW). The candidate will be responsible for evaluating existing data architecture, designing scalable data models, assessing data integration across clinical, operational and financial domains, and establishing data governance and data quality standards.

Key Responsibilities :

- Assess and review the existing Enterprise Analytic Data Warehouse architecture, database structures and data integration processes.

- Design and improve enterprise data models covering clinical, operational, financial and revenue-cycle information.

- Define data architecture standards, database structures, data relationships and integration strategies.

- Evaluate data flows between source systems and the data warehouse.

- Design and review source-to-target mappings and data lineage.

- Identify architectural gaps affecting data completeness, consistency, integrity and reporting accuracy.

- Establish standardized data definitions, data governance practices and metadata management.

- Ensure consistent patient, facility, payer and other critical identifiers across different datasets.

- Support integration of billing, claims, payment, denial and accounts receivable (AR) data.

- Work with SQL and Python-based data processing solutions to investigate and validate data structures.

- Recommend improvements to warehouse scalability, performance, reliability and maintainability.

- Develop a prioritized architecture and modernization roadmap for future implementation.

- Coordinate with data engineers, analytics engineers and business stakeholders.

Required Technical Skills :

- Strong experience in Data Architecture and Enterprise Data Warehousing.

- Advanced SQL and relational database concepts.

- Experience with data modelling (conceptual, logical and physical).

- Knowledge of ETL/ELT pipelines and data integration.

- Experience with data profiling, data lineage and metadata management.

- Understanding of data governance, data quality and data validation frameworks.

- Experience working with large and complex datasets.

- Python knowledge for data analysis and validation.

- Experience with cloud-based data platforms or modern data warehouse technologies.

Preferred Skills :

- Experience with Databricks, Azure, AWS or similar cloud data platforms.

- Experience with healthcare data warehouses.

- Knowledge of clinical, financial, billing and claims datasets.

- Understanding of HIPAA, PHI and healthcare data security principles.

- Experience with healthcare analytics, reimbursement and revenue-cycle data.