Data Architect Senior

How to Apply

A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.

Have questions about the role or want to learn more before applying? 

Join our informal, open forum Teams session to connect with the hiring team! Drop in at any time during the hour and stay as long as you'd like - whether you have specific questions or just want to listen in. 

Monday, November 17 | 12:00 PM - 1:00 PM EST | Click Here to Join Monday's Teams Meeting

Job Summary

The Supply Chain Services Data Architect Senior is responsible for designing, constructing, migrating, and maintaining robust, scalable data models and data warehousing solutions to deliver comprehensive, high-quality supply chain data across University of Michigan Health. This position reports to the Supply Chain Services Applications and Analytics Solutions Manager. Leveraging both traditional (on-premises, SQL Server, SSIS, Oracle) and modern cloud analytics stacks (Microsoft Fabric, Power BI, Azure Synapse, Purview), this role empowers analytics, reporting, and advanced artificial intelligence (AI) and machine learning (ML) strategies used for standalone supply chain insights or integrated with clinical data to support a clinically integrated supply chain.

The Data Architect Senior works collaboratively with application developers, analytics teams, and supply chain stakeholders to ensure data accuracy, performance, security, and accessibility, providing the critical infrastructure that supports patient care, operational efficiency, cost containment, and organizational strategy. This role is ideal for a technically skilled data professional passionate about designing systems that transform complex data into actionable insights for both clinical and supply chain excellence, exercising sound independent judgment on complex, high-impact projects.

Mission Statement

Michigan Medicine improves the health of patients, populations and communities through excellence in education, patient care, community service, research and technology development, and through leadership activities in Michigan, nationally and internationally.  Our mission is guided by our Strategic Principles and has three critical components; patient care, education and research that together enhance our contribution to society.

Why Join Michigan Medicine?

Michigan Medicine is one of the largest health care complexes in the world and has been the site of many groundbreaking medical and technological advancements since the opening of the U-M Medical School in 1850. Michigan Medicine is comprised of over 30,000 employees and our vision is to attract, inspire, and develop outstanding people in medicine, sciences, and healthcare to become one of the world’s most distinguished academic health systems.  In some way, great or small, every person here helps to advance this world-class institution. Work at Michigan Medicine and become a victor for the greater good.

What Benefits can you Look Forward to?

• Excellent medical, dental and vision coverage effective on your very first day
• 2:1 Match on retirement savings

Responsibilities*

Database Design & Architecture

• Design, construct, migrate, and maintain scalable, normalized, well-documented relational and cloud-based data warehouses and data platforms (including SQL Server, Oracle, Azure Synapse, Fabric Lakehouse, and Power BI Dataflows), focused on supply chain domains such as procurement, inventory, distribution, contracts, and finance.
• Develop and optimize SQL Server (on-prem and Azure SQL), Oracle, and associated semantic models supporting custom applications and enterprise analytics dashboards.
• Partner with application developers and analytics leads to create data marts and semantic layers bridging raw, modeled, and clinical data to business processes and end-user applications in both legacy and cloud environments.
• Develop, implement, and refine comprehensive data models (conceptual, logical, and physical) supporting predictive analytics, demand forecasting, and process optimization, leveraging both traditional and cloud tools.
• Build and manage robust data acquisition, access, archiving, recovery, and ETL/ELT strategies using SSIS, Python, Azure Data Factory, and Microsoft Fabric Data Factory to ensure efficient, secure data availability.
• Implementing Master Data Management (MDM) within supply chain services

Data Engineering & Integration

• Build, monitor, and maintain resilient ETL/ELT pipelines and dataflows using SSIS, Python, Tableau Prep, Azure Data Factory, and Microsoft Fabric, ensuring reliable batch and real-time data ingestion and transformation from internal and external sources.
• Collaborate with IT and data governance teams to facilitate consistent and accurate ingestion of data feeds from vendors, third-party tools, clinical systems, and cloud sources, complying with institutional governance standards.
• Develop APIs or middleware for real-time or near-real-time data interchange across diverse platforms as required.
• Lead onboarding and integration of new data sources, ensuring architecture compatibility and maintaining best practices in data lineage and quality.

Performance, Security & Governance

• Optimize queries, indexing strategies, caching, and data models across on-premises and cloud platforms to support high performance, analytics, and dashboarding tools.
• Implement scalable data validation, exception handling, and auditing processes for critical applications (item intake, product conversion, contract compliance), using both legacy and modern practices.
• Maintain comprehensive technical documentation and metadata for all architecture, processes, and models, adhering to institutional governance and regulatory requirements such as HIPAA.
• Enforce robust security practices, PHI/PII protection, HIPAA compliance, row-level security, and least-privilege access in both on-premises and cloud environments.
• Support and document continuous improvement initiatives incorporating AI/ML advances (such as natural language processing and embedded AI) to boost performance, security, accessibility, and functionality of supply chain data solutions.
• As a Data Architect, you have the expertise with the DAMA framework to deliver security plans, data architecture diagrams, data dictionaries, data models, and governance policies.

Strategic Partnership, Innovation & Education

• Collaborate with supply chain stakeholders, Solutions Managers, and Value Analysis teams to design analytical tools and visualizations supporting clinical decision-making, utilization reviews, and cost savings initiatives.
• Co-develop next-generation supply chain analytics leveraging predictive modeling, Power BI, Microsoft Fabric, AI, and natural language processing for advanced projects (e.g., semantic item classification, opportunity identification, intelligent routing).
• Lead or co-lead migration and modernization efforts, integrating fragmented or siloed systems and legacy workflows (Oracle, SQL Server, Tableau Prep, SSIS) into unified, scalable, cloud-enabled architectures.
• Deliver consultative expertise, training, and support for supply chain, data science, and analytics teams adopting both legacy and cloud BI/AI applications.
• Work independently on complex projects with minimal supervision, making impactful decisions that support both business and clinical operations.

Required Qualifications*

• Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or a combination of degree and relevant work experience.
• 4-5 years of hands-on experience in data architecture, data modeling, data warehousing, and database engineering (preferably in healthcare or supply chain domains).
• Proven expertise with Microsoft SQL Server, SSIS, Oracle, Tableau Prep, and other RDBMS platforms; demonstrated experience with cloud technologies and platforms (Azure Synapse, Power BI, Microsoft Fabric, AWS, or Google Cloud Platform).
• Experience designing, constructing, and maintaining scalable data warehouses, data models, and AI/ML-ready solutions for operational and analytical use.
• Proficiency in modern data modeling, normalization, ETL/ELT tools, and relational/cloud database design.
• Experience supporting custom or low-code applications; strong backend design and data provisioning skills for analytics platforms.
• Excellent analytical, problem-solving, project management, and communication skills.
• Ability to work independently and exercise sound technical judgment on complex assignments.

Desired Qualifications*

• Master's degree in a related field (e.g., Information Systems, Health Informatics, Data Engineering, Supply Chain Management).
• Direct experience supporting healthcare supply chain analytics, data workflows, and reporting.
• Familiarity with healthcare ERP systems, supply chain management principles, item master maintenance, value analysis, and integration of clinical and supply chain datasets.
• Deep experience with cloud-based data platforms (Azure, Fabric, Power BI) including migration, optimization, and cross-platform integration.
• DAMA-CDMP, Microsoft Azure/Fabric-related, or Tableau Desktop Certified Professional certification.  PMP or PRINCE2 certification preferred.
• Knowledge of enterprise data governance, metadata management, regulatory compliance (HIPAA), and best practices for comprehensive technical documentation.
• Exposure to AI/ML tools (Azure Machine Learning, Copilot, Power BI AI integrations), data science platforms, and their practical application in supply chain or healthcare operational analytics.
• Experienced with version control systems such as Git, including check-in/check-out processes, production release management, technical documentation, and collaborative analytics development on cloud platforms.
• Experienced with NoSQL databases (e.g., MongoDB, Redis) and skilled in determining appropriate use cases compared to traditional RDBMS.
• Familiarity with Lean Six Sigma, Agile or other process improvement methodologies.
• Ability to explain complex data systems and architectures to non-technical or executive stakeholders.
• Experience with delivering comprehensive Solution Design and Technical Documentation, including solution design documents, integration diagrams, technical specifications

Modes of Work

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes.

• This position follows a hybrid work schedule, requiring a minimum of three days per week (Tuesday through Thursday) on-site at the Ann Arbor office on Green Road, with the option to work remotely from home up to two days per week.

Background Screening

Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings.  Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.

Application Deadline

Job openings are posted for a minimum of seven calendar days.  The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.

U-M EEO Statement

The University of Michigan is an equal employment opportunity employer.