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.
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.
Job Summary
The Supply Chain Services Data Engineer 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 through the Innovation Office and is dedicated to supply chain solutions.
Working within an established modern analytics-as-code stack (PostgreSQL, dbt, Prefect, Python, Git/GitLab CI) and integrating data from diverse sources (SQL databases, APIs, flat files, SFTP feeds), this role empowers analytics, reporting, and advanced AI/ML strategies used for standalone supply chain insights or integrated with clinical data to support a clinically integrated supply chain. The Data Engineer focuses on building and maintaining production-grade, well-documented data pipelines and repositories.
The Data Engineer works collaboratively with application developers, analytics teams, solution architects, 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.
NOTE: A cover letter is required for this application. In your cover letter, please address how you meet the required qualifications and your interest in the position.
Responsibilities*
Data Engineering, Modeling & Integration
- Design, construct, migrate, and maintain scalable, well-documented relational data warehouses and analytics platforms focused on supply chain domains (procurement, inventory, distribution, contracts, finance) across multiple enterprise sites.
- Develop and refine comprehensive data models (conceptual, logical, physical) and transformation layers (staging, intermediate, marts) bridging raw data to business processes and end-user applications.
- Build, monitor, and maintain resilient ELT pipelines and orchestration flows using Prefect and Python, ensuring reliable batch data ingestion and transformation from internal and external sources across multiple enterprise sites and ERP systems.
- Collaborate with IT and data governance teams to facilitate consistent and accurate ingestion of data feeds from vendors, third-party tools, clinical systems, and enterprise sources - including regional site data (e.g., via SFTP) - complying with institutional governance standards.
- Lead onboarding and integration of new data sources, ensuring architecture compatibility and maintaining best practices in data lineage and quality.
- Support Master Data Management (MDM) initiatives within supply chain services, including golden-record strategies across a multi-ERP environment.
- Contribute to cross-departmental data unification efforts, enabling coherent data feeds across supply chain, pharmacy, finance, and other health system domains.
Performance, Security & Governance
- Optimize queries, indexing strategies, caching, and transformation models to support high-performance analytics and dashboarding tools.
- Implement scalable data validation, exception handling, and auditing processes for critical applications, using automated testing and task-level monitoring.
- Maintain comprehensive technical documentation and metadata for all architecture, processes, and models - including schema definitions, documentation files, and institutional governance artifacts - adhering to regulatory requirements such as HIPAA.
- Enforce robust security practices, PHI/PII protection, HIPAA compliance, row-level security, and least-privilege access across all database 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.
Strategic Partnership, Innovation & Education
- Collaborate with supply chain stakeholders, Solutions Managers, and Value Analysis teams to design data infrastructure supporting clinical decision-making, utilization reviews, and cost savings initiatives.
- Co-develop next-generation supply chain analytics leveraging predictive modeling, semantic models, AI, and natural language processing for advanced projects (e.g., semantic item classification, opportunity identification, intelligent routing, contract data extraction).
- Support migration and modernization efforts, integrating fragmented or siloed systems and legacy workflows (legacy ETL, manual extracts) into unified, code-versioned analytics architectures.
- Deliver consultative expertise, training, and support for supply chain and analytics teams adopting modern analytics-as-code and AI/ML tooling.
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, or data engineering (preferably in healthcare or supply chain domains).
- Proven expertise working across multiple database platforms (e.g., PostgreSQL, SQL Server, Oracle) in a heterogeneous environment.
- Experience with a workflow orchestration tool such as Prefect, Airflow, or Dagster for building and managing data pipelines.
- Strong Python proficiency for data engineering, pipeline development, and automation.
- Proficiency in modern data modeling, normalization, ELT patterns, and relational database design.
- Experience with Git-based version control and CI/CD workflows (GitLab CI or equivalent).
- Demonstrated proficiency with AI and experience working with agentic coding tools (e.g., Cursor, OpenAI Codex, Claude Code, Anti-Gravity) to accelerate development workflows.
- Excellent analytical, problem-solving, 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.
- Experience working in a multi-site or multi-ERP healthcare environment.
- Experience with dbt (or equivalent transformation framework) for building tested, documented, layered data models - including docs, lineage, semantic models, and testing strategies (schema tests, data quality tests, custom macros).
- Experience with Prefect Cloud (deployments, work pools, schedules, parameterized flows) or equivalent managed orchestration platform.
- Familiarity with Power BI or other enterprise BI platforms for understanding downstream analytics consumption.
- DAMA-CDMP certification or equivalent data governance credential.
- Knowledge of enterprise data governance, metadata management, regulatory compliance (HIPAA), and best practices for comprehensive technical documentation.
- Deep experience applying AI/ML tools (LLM integrations, AI-assisted analytics, agentic development environments) to supply chain, healthcare operational analytics, or data engineering workflows.
- Ability to explain complex data systems and architectures to non-technical or executive stakeholders.
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
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.