Data Architect

Role Summary

Senior architecture role focused on modern healthcare data platforms, Medicaid/T-MSIS domain expertise, and large-scale modernization using AWS Databricks.

Roles & Responsibilities

• Define scalable data architecture patterns using AWS Databricks, PySpark, Spark SQL, Delta Lake, and lakehouse / medallion architecture principles.
• Design canonical/conformed data models, metadata-driven transformation patterns, reusable rule frameworks, and governed reference-data structures.
• Translate T-MSIS and Medicaid business requirements into technical architecture and data-model decisions.
• Guide modernization of legacy ETL and batch solutions into cloud-native Databricks implementations.
• Provide architectural guidance for source-to-target mapping, state-specific rules, validation, reconciliation, lineage, audit, and data governance.
• Review technical designs, data models, transformation logic, and engineering standards.
• Work closely with business SMEs, mapping analysts, data engineers, QA, and platform teams to resolve complex data and domain issues.
• Mentor engineering teams and provide technical leadership on performance, scalability, maintainability, and security.

Required Skills & Experience

• 10+ years of data engineering / architecture experience, including 3+ years in a senior or lead architect role.
• Strong hands-on experience with AWS Databricks, PySpark, Spark SQL, Delta Lake, Databricks Workflows, and lakehouse / medallion architectures.
• Strong understanding of AWS data-platform services and integration patterns, including S3, IAM, networking/security concepts, and cloud data movement.
• Strong data modeling experience covering raw, conformed, curated, and regulatory-reporting data layers.
• Experience designing metadata-driven / configuration-driven transformation and business-rules frameworks.
• Experience with Unity Catalog, data lineage, access controls, auditability, and governed reference data.
• Strong SQL and experience with Oracle, SQL Server, DB2, flat files, and enterprise source systems.
• Experience modernizing legacy ETL platforms such as DataStage, SSIS, Informatica, C/Linux, COBOL, or custom batch frameworks.
• Experience with Git, CI/CD, code review, automated testing, and deployment practices for Databricks.
• Strong communication skills and ability to convert complex business and regulatory requirements into practical architecture.