Data Engineer — Hybrid Research Data Pipelines

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

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.