Senior Data Engineer - Healthcare AI

UT MD Anderson is a cancer center focused on advancing healthcare and cancer care through responsible innovation. The Senior Data Engineer will design, build, and operate secure, scalable data infrastructure and AI/ML pipelines, including feature and vector stores, while supporting governance, compliance, monitoring, and collaboration across technical and clinical teams.

Responsibilities:

• Design, implement, and maintain batch and streaming pipelines for machine learning training, deployment, inference, and monitoring
• Utilize Azure, Dataiku, and open-source tools to deliver scalable and reliable AI/ML data solutions
• Deploy and manage raw data stores for production AI/ML workloads
• Develop and maintain feature stores to support machine learning lifecycle requirements
• Manage vector stores to provide fast and reliable access for production AI systems
• Automate deployments using Infrastructure-as-Code methodologies
• Implement CI/CD workflows to improve operational efficiency and deployment reliability
• Establish data validation processes to improve accuracy and consistency
• Implement lineage, anomaly detection, and drift monitoring capabilities for compliant and trusted data operations
• Enforce encryption controls across data platforms and pipelines
• Implement role-based access controls, tokenization, and audit logging
• Support HIPAA and HITRUST compliance requirements while enabling scalable AI operations
• Manage monitoring, alerting, incident response, and continuous improvement activities
• Own data pipelines and infrastructure throughout the operational lifecycle
• Partner with data engineers, machine learning engineers, data scientists, clinicians, and technology stakeholders to deliver scalable AI solutions
• Mentor team members and promote data engineering best practices across the organization
• Perform additional duties as assigned in support of departmental objectives

Requirements:

• Required Education: Bachelor's degree
• Required Experience: Five years of relevant information technology experience
• May substitute required education with years of related experience on a one-to-one basis
• With preferred degree, three years of experience required
• The ideal candidate brings advanced technical expertise in data engineering, healthcare data management, and AI/ML enablement
• Preferred qualifications include experience with Python, SQL, Spark, Azure services, Infrastructure-as-Code technologies, CI/CD workflows, healthcare data standards such as HL7, FHIR, and DICOM, HIPAA/HITRUST compliance practices, feature and vector store management, leadership experience, and the ability to communicate effectively with both technical and non-technical stakeholders
• Preferred Education: Master's Level Degree
• Preferred Certification: Must obtain at least one Epic Data Model certification (Clinical, Access, or Revenue) issued by Epic within 180 days of date of entry into job
• Azure Data Engineer Associate (DP-203)
• EPIC Cogito Certification
• HIPAA Privacy & Security Certification
• HL7/FHIR Certification
• Preferred Experience: Healthcare experience in AI/ML space is a must, two years of industry experience in a Senior Data Scientist role, knowledge of data privacy, security, and HIPAA compliance in healthcare