Data Engineer

University of Wisconsin–Madison; Madison (WI); Hybrid; USD 61,000 - 75,000; Full time

Benefits offered by this job

Generous paid time off

Health/dental/vision/life insurance

Tax-advantaged savings accounts

Wisconsin Retirement System (WRS)

Job summary

University of Wisconsin–Madison is seeking a Data Engineer for the MIDUS Biomarker project in Madison, WI. The hybrid role coordinates electronic data across waves, ensuring organization, quality control, and preparation for cleaning and release of datasets.

You will collaborate with data scientists and researchers to build scalable data management architectures, implement analysis steps, and optimize pipeline performance while supervising student staff as needed.

Qualifications

• Bachelor's degree required.
• Experience with REDCap.
• 1+ year of work with research projects.
• Experience with data cleaning and quality assurance.
• Experience with longitudinal databases, especially survey data.
• Excellent verbal and written communication skills.
• Experience with SPSS.
• Familiarity with Python and SQL.

Responsibilities

• Build reproducible data preparation and analysis pipelines across waves.
• Prepare datasets for current and future analysis, including cleaning and QA, transformations, restructuring, and integration of multiple sources.
• Develop and maintain large-scale data management and analysis architectures.
• Collaborate with data scientists and researchers to implement analysis steps using scalable technologies.
• Select appropriate technologies and optimize pipeline performance.
• Supervise day-to-day activities of student staff related to data entry (if required).

Skills

REDCap

Data cleaning

Longitudinal data

Survey data

SPSS

Python

SQL

Verbal & written comms

Education

Bachelor's degree

Tools

SPSS

Python

REDCap

SQL

Job description

Support high-impact research with the MIDUS Biomarker project at the University of Wisconsin–Madison (Office of the Vice Chancellor for Research, Institute on Aging). This Data Engineer role in Madison, WI (hybrid) helps coordinate electronic data and materials across multiple waves, including organization, quality control, and preparation for cleaning and release. The position offers generous paid time off, comprehensive health/dental/vision/life insurance, tax-advantaged savings accounts, and participation in the Wisconsin Retirement System (WRS) pension fund.

Compensation starts at USD 68,000 per year (minimum annual salary), with negotiation based on experience and qualifications. Appointment may be full-time or part-time, between 75–100% (approximately 30 to 40 hours per week), determined in collaboration with the supervisor. The schedule runs Monday to Friday within normal business hours, and most work is performed in person onsite at a campus work location. After a trial period, remote work of up to one day per week may be considered with supervisor approval.

What you’ll do

• Build reproducible data preparation and analysis pipelines that can process similar datasets automatically.
• Prepare datasets for current and future analysis, including cleaning/quality assurance, transformations, restructuring, and integration of multiple data sources; use technologies that support data at scale.
• Develop, construct, test, and maintain large-scale data management and analysis architectures.
• Implement analysis steps in collaboration with data scientists, statisticians, and/or other researchers, potentially using technologies that support data at scale.
• Select appropriate technologies and optimize pipeline performance.
• Supervise the day-to-day activities of student staff related to data entry (may be required).

What you bring

• Experience with REDCap.
• 1 or more years of work experience with research projects.
• Experience with data cleaning and quality assurance.
• Experience with longitudinal databases, especially survey data.
• Excellent verbal and written communication skills.
• Experience with SPSS.
• Bachelor’s degree required.

Tools and technologies

• SPSS
• Python
• REDCap
• SQL

Education and preferred qualifications

Graduate work or a degree in epidemiology, population health, social sciences, or information science is preferred. Preferred qualifications also include familiarity with Python and SQL, strong organizational skills for managing multiple priorities with attention to detail, experience training and supervising undergraduate student staff, and the ability to work independently and in a team environment.