Part-Time Data Steward & Analytics Coordinator

University of Miami; United States; On-site; USD 34,000 - 55,000; Part time

Benefits offered by this job

Medical insurance

Dental insurance

Tuition remission

Job summary

The University of Miami/UHealth Department of Neurology has a Part Time TEMP Data Management Coordinator opening at UHealth. The role focuses on end-to-end data handling from REDCap to analysis-ready tables in Azure, with HIPAA-compliant practices and reporting support for multiple studies.

The incumbent will build and maintain data collection tools, run Python pipelines, generate reports, and collaborate with study teams to resolve data issues, ensuring accurate, audit-ready datasets.

Qualifications

• Data lifecycle knowledge in research data domains.
• Experience with PHI handling and IRB-driven data management.
• Ability to design validation checks and reconcile data sources.

Responsibilities

• Review research proposals, awards, contracts, and related data documents.
• Generate reports and analyze data for planning and reporting.
• Identify and resolve data bugs and anomalies.
• Create reports for user departments and exports for study teams.
• Build and manage REDCap projects, instruments and surveys.
• Run Python pipelines pulling data into Azure data lake.
• Maintain data notebooks and metadata using Synapse and Delta patterns.
• Ensure HIPAA compliance and data de-identification as required.

Skills

REDCap

Python

PySpark

Azure

Data governance

HIPAA compliance

Data quality

Data analysis

Report generation

SQL/ databases

Education

High School diploma or equivalent

Tools

REDCap

Azure

Synapse

Delta tables

Microsoft Power BI

Job description

The University of Miami/UHealth Department of Neurology has a Part Time TEMP Data Management Coordinator opening at UHealth. The role focuses on end-to-end data handling from REDCap to analysis-ready tables in Azure, with HIPAA-compliant practices and reporting support for multiple studies.

The incumbent will build and maintain data collection tools, run Python pipelines, generate reports, and collaborate with study teams to resolve data issues, ensuring accurate, audit-ready datasets.