Data Engineer - Enterprise Data Engineering & Analytics

UT MD Anderson is a leading institution focused on cancer care, research, education, and prevention. The Data Engineer role is essential for supporting digital initiatives through the design and delivery of scalable data solutions, ensuring high-quality data integration and analytics delivery.

Responsibilities:

• Participate in end-to-end solution delivery to enhance information capabilities and data value across the institution
• Support data ingestion, ingress, egress, curation, transformation, modeling, and visualization within the Context Engine framework
• Integrate data governance processes ensuring tracking of provenance, data security, quality, and ontology
• Contribute to planning, architecture, analysis, design, and build of data pipelines in collaboration with IS, Data Offices, and governance teams
• Support pipelines across all stages from data acquisition to consumption for use-case-driven analytics
• Develop repeatable solution designs and data models supporting scalable analytics deliverables
• Build data curation pipelines including profiling, cleansing, transforming, standardizing, harmonizing, validating, and aggregating data
• Monitor and maintain data quality across enterprise systems
• Incorporate metadata management and governance standards into all data processes
• Promote modern tools, automation, and architectures to reduce manual and error-prone data integration tasks
• Adhere to IS division procedures and institutional data strategy standards including governance oversight
• Support documentation for enhancements and new technologies
• Follow change control processes and participate in change control audits
• Perform quality control, testing, and peer reviews of data solutions
• Assist in managing analytics system updates and new releases
• Ensure compliance with regulatory requirements, quality standards, and best practices
• Collaborate with internal and external stakeholders for solution validation
• Participate in after-hours support and downtime procedures
• Train data scientists, analysts, and end users on data pipeline utilization and preparation techniques
• Assist in developing training plans for Context Engine tools in partnership with training teams
• Deliver institutional, departmental, and individual training on data engineering deliverables
• Support the development of training curricula with system experts
• Build strong partnerships with Enterprise Development & Integration and Data Science teams
• Support liaison relationships across departments and IS teams
• Deliver effective technical solutions aligned with customer needs
• Provide responsive support and maintain high standards of customer service
• Promote integrity, trust, and respect in all interactions
• Strengthen collaborative relationships with stakeholders and team members
• Deliver innovative, high-quality, and sustainable IT solutions
• Demonstrate commitment to continuous improvement and operational excellence

Requirements:

• Bachelor's Degree
• 2 years Clinical, relevant healthcare information technology, or relevant business experience
• With preferred degree, no experience required
• EPIC - EPIC Certification Must obtain at least one Epic Data Model certification (Clinical, Access, or Revenue) issued by Epic within 180 Days
• Master's Degree Business Analytics, Computer Science, Information Technology, Data Science, or related
• Experience building end to end data pipelines, Power BI, Microsoft Fabric, Palantir Foundry
• Certification: Caboodle