A cover letter is required for consideration and should be attached as the first page of your resume. The cover letter should describe your specific interest in the position and highlight skills and experience that directly relate to this role.
Join the Pharmacy Data Solutions team at Michigan Medicine as a Data Architect Senior, where you will serve as the technical owner of the pharmacy analytics data platform supporting operational, financial, and clinical decision-making across pharmacy services.
This role is responsible for the design, evolution, and modernization of the pharmacy data ecosystem, including data warehouse architecture, dimensional data modeling, pipeline development, and platform performance optimization. The platform supports enterprise dashboards, KPI reporting, and advanced analytics initiatives.
This is a hands-on technical leadership role operating within a small, high-autonomy team. The Data Architect Senior is expected to balance architecture strategy with practical delivery, owning initiatives end-to-end while contributing directly to implementation, QA, and analytics support when needed.
This position reports to the Director of Pharmacy Analytics.
Data Platform Ownership & Architecture
- Serve as the technical owner of the pharmacy analytics data platform, ensuring long-term scalability, maintainability, and reliability.
- Define and evolve data architecture standards, modeling approaches, and integration patterns.
- Own and continuously improve data models using dbt and modern analytics engineering practices.
- Identify and reduce technical debt through thoughtful model redesign and architectural improvements.
- Drive modernization efforts by evaluating and adopting new tools, patterns, and technologies where appropriate.
Data Integration & Pipeline Engineering
- Design, build, and maintain ETL/ELT pipelines integrating financial, operational, clinical, and other pharmacy data sources.
- Develop data workflows using Python, dbt, and orchestration tools such as Prefect or similar platforms.
- Establish best practices for data ingestion, transformation, archival, recovery, and lifecycle management across multiple database platforms.
- Continuously improve pipeline performance, reliability, and operational efficiency.
Data Governance, Quality & Documentation
- Establish and enforce data standards, naming conventions, and engineering best practices.
- Implement automated testing, validation, and monitoring frameworks to ensure data accuracy and reliability.
- Monitor and resolve data quality issues through root-cause analysis and reconciliation processes.
- Maintain clear and comprehensive documentation covering architecture, data models, lineage, and workflows.
- Ensure compliance with HIPAA and institutional data governance requirements.
End-to-End Delivery & Technical Leadership
- Lead end-to-end data initiatives from architecture and design through implementation, testing, and production deployment.
- Participate directly in development work when needed, including data modeling, pipeline development, QA, and troubleshooting.
- Provide technical leadership across the analytics lifecycle.
- Occasionally support dashboard development, reporting, or visualization efforts (e.g., Tableau) to ensure successful delivery.
- Collaborate closely with analysts, pharmacy leadership, and operational stakeholders to align technical solutions with business needs.
Engineering Excellence & Innovation
- Maintain version-controlled, peer-reviewed code using Git-based workflows and CI/CD pipelines.
- Promote modern development practices, including automation and AI-assisted development tools where appropriate.
- Evaluate emerging technologies and recommend solutions that improve productivity, performance,
