Data Architect Senior

The University of Michigan Department of Internal Medicine seeks a research data engineer and analyst to support clinical and microbiome research, working with investigators in infectious diseases and pulmonary and critical care medicine. You will build and validate clinical research datasets, develop reproducible SQL and R or Python workflows, and conduct analyses in collaboration with the investigators., Responsibilities are the same at both levels. At the Intermediate level, the position works with closer guidance from the investigators on study design, cohort definitions, and analytic approach.

Clinical data engineering 45 percent

Build and maintain workflows using the U-M Research Data Warehouse and other approved clinical data sources. Link patient, encounter, medication, laboratory, and outcome records into validated study datasets. Develop reusable SQL queries, automated quality checks, and documented procedures for updating datasets. Investigate missing data, duplicate records, and inconsistencies in units or timing.

Clinical research analysis 25 percent

Translate study questions into cohort definitions and analysis variables with the investigators. Conduct descriptive and regression analyses in R or Python, prepare figures and tables, and investigate unexpected results. Work with investigators and statistical collaborators on methods and interpretation, and contribute to methods and results documentation.

Microbiome analysis and training 20 percent

Learn and apply the laboratory’s established 16S rRNA gene analysis workflow. Process sequencing data, perform quality control, organize sample metadata, and conduct microbial community analyses in R. Integrate microbiome findings with approved clinical datasets under scientific guidance.

Documentation and collaboration 10 percent

Maintain version-controlled code, data dictionaries, and clear analysis records. Coordinate priorities with both investigators, communicate progress and data limitations, and help collaborators use reproducible research practices., 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 Reporting 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.

• Bachelor’s degree in computer science, data science, biomedical informatics, statistics, engineering, or a related quantitative field, or an equivalent combination of education and experience.
• Proficiency in SQL, including joins across multiple tables and validation of relationships and timing across records.
• Proficiency in R or Python and willingness to work in the laboratory’s R-based analytical workflows.
• Experience building and documenting datasets or analysis code using version control.
• Ability to explain technical issues to clinical collaborators and to handle sensitive research data in approved computing environments.
• Willingness to learn microbiome analysis methods and complete the training required for clinical data access.

Senior level

• 3+ years of experience in data engineering, analytical programming, or research data management.
• Experience with clinical, electronic health record, or other longitudinal health data.
• Advanced SQL skills, including window functions and efficient querying of large tables.
• Demonstrated ability to independently build, validate, maintain, and document reusable datasets and analysis workflows with systematic quality checks.
• Ability to manage projects and set priorities across multiple studies.

Intermediate level

• 1-3 years of experience in data engineering, analytical programming, or research data management.

Desired Qualifications*

• Master’s degree in a relevant quantitative or computing field.
• Experience with longitudinal clinical or electronic health record data.
• Experience with the U-M Research Data Warehouse, DeID RDW, DataDirect, or comparable clinical data warehouses; familiarity with Epic data and clinical terminology.
• Experience with regression, longitudinal or survival analysis, epidemiologic study design, and preparation of publication-quality figures and tables.
• Experience with 16S analysis, mothur, R/vegan, or related microbiome methods, including sequencing controls and sample metadata.
• Experience linking clinical records to biospecimen data and working in Unix, Linux, or comparable research computing environments.

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.