Lead - Biomedical Data Factory Team

Medical University of South Carolina; Charleston, Northern (SC, KY); Hybrid; USD 130,000 - 170,000; Full time

Job summary

Medical University of South Carolina (MUSC) seeks a Lead of the Clinical Data Factory to advance the data ecosystem powering AI development. You will ensure PI/PHI‑compliant synthetic data pipelines, support model-training readiness, and maintain data availability in alignment with IS architecture.

You will lead a team of data engineers and architects, collaborate with the AI Center, and drive governance to ensure compliant, high‑integrity data for experimentation and modeling efforts.

Qualifications

• Master’s degree required.
• 2–3 years of relevant experience with some leadership exposure.
• Experience in data engineering, synthetic data pipelines, ETL/ELT workflows, or regulated healthcare data systems.
• Familiarity with PI/PHI handling, HIPAA, or regulated‑data architectures preferred.

Responsibilities

• Lead Synthetic Data Pipeline Management & Compliance initiatives and ensure PI/PHI compliant data flows.
• Oversee System Architecture, maintenance and enhancements for AI Center tools and data infra.
• Provide Team Leadership & technical guidance to Jr. Data Engineers and Architects.
• Collaborate with AI project teams to support data provisioning, synthetic layering and model experimentation.
• Support Governance, Quality & Model Integrity aligning with IS Guidance and policy.

Skills

Data engineering

Synthetic data pipelines

ETL/ELT workflows

Leadership

Education

Master’s degree

Job description

Job Description Summary

The Lead of the Clinical Data Factory supports the data ecosystem that powers MUSC’s AI development workflows. This role ensures PI/PHI‑compliant synthetic data pipelines, model‑training readiness, system stability, and data availability by working w/IS architecture to keep the mini-arch ahead of major changes for continued workflow. The Lead works closely with Central IS Architecture and Security, and the AI Center to maintain an emergent AI architecture that reduces load on central IT while enabling rapid experimentation and compliant model development.

Entity University Medical Associates (UMA) Only Employees and Financials

Worker Type Employee

Worker Sub-Type Classified

Cost Center CC005532 EVPAA - Center for Artificial Intelligence

Pay Rate Type Salary

Pay Grade Health-34

Scheduled Weekly Hours 40

Work Shift

Job Description

Primary Areas of Responsibility (with % Allocation)

1. Synthetic Data Pipeline Management & Compliance – 40%

• Maintain high‑performance data pipelines meeting PI/PHI compliance standards.
• Audit, monitor, and improve data quality, performance, and lineage.
• Support model‑training workflows with high‑integrity synthetic datasets.
• Ensure operational compliance, and follow through with IS Strategies and Approaches

2. System Architecture, Maintenance & Enhancement – 25%

• Oversee lifecycle maintenance of AI Center Built Tools, patching, and upgrades to mini data infrastructure.
• Partner with enterprise architecture teams to ensure alignment with evolving systems.
• Communicate risks, dependencies, and required enhancements proactively.

3. Team Leadership & Technical Guidance – 20%

• Lead and mentor Jr. Data Engineers and Jr. Architects.
• Maintain documentation, operational workflows, and technical standards.
• Coordinate team activities to meet service and uptime commitments.

4. Integration with AI Project Teams – 10%

• Collaborate with AI Strategy & Ops, Research and AI Incubation teams to ensure data needs are met.
• Provide technical support for data provisioning, synthetic layering, and model experimentation for the AI Center activities.

5. Governance, Quality & Model Integrity Support – 5%

• Maintain data governance practices that support ethical model development.
• Support model integrity monitoring and data risk mitigation in conjunction w/IS Guidance and Policy

Key Annual Performance Objectives

• Meet synthetic data KPIs for quality, performance, and service uptime.
• Reduce dependency on core IT architecture for AI model development.
• Maintain compliance and operational stability of the synthetic data ecosystem.

Additional Job Description

If you like working with energetic enthusiastic individuals, you will enjoy your career with us!

Required Qualifications

• Education: Master’s degree required.
• Experience: 2–3 years of relevant experience with some leadership exposure, ideally in data engineering, architecture, synthetic data systems, or compliant data environments.
• Technical Capability: Experience in data engineering, synthetic data pipelines, ETL/ELT workflows, or regulated healthcare data systems.
• Compliance Knowledge: Familiarity with PI/PHI handling, HIPAA, or regulated‑data architectures preferred.
• Leadership: Ability to mentor junior engineers/architects and coordinate technical backlog or system maintenance cycles.

The Medical University of South Carolina is an Equal Opportunity Employer. MUSC does not discriminate on the basis of race, color, religion or belief, age, sex, national origin, gender identity, sexual orientation, disability, protected veteran status, family or parental status, or any other status protected by state laws and/or federal regulations. All qualified applicants are encouraged to apply and will receive consideration for employment based upon applicable qualifications, merit and business need.

Medical University of South Carolina participates in the federal E-Verify program to confirm the identity and employment authorization of all newly hired employees. For further information about the E-Verify program, please click here: http://www.uscis.gov/e-verify/employees