Principal Data Engineer

UT MD Anderson is a leading cancer center that focuses on innovation in healthcare and research. The Principal Data Engineer will operationalize data engineering and analytics initiatives, leading the design and development of enterprise data solutions while ensuring compliance with governance and quality standards.

Responsibilities:

• Lead end-to-end solution delivery that increases information capabilities and realizes data value across the institution
• Integrate data governance processes through ingestion, ingress, egress, curation, pipeline development, transformation, modeling, visualization, and insights delivery
• Lead planning, architecture, analysis, design, and development of enterprise data pipelines and solutions across the Context Engine
• Partner with Information Services, Data Offices, Data Governance teams, and other stakeholders to manage institutional data efficiently
• Lead development and maintenance of end-to-end data pipelines from acquisition through integration and consumption
• Build and incorporate repeatable solution designs and reusable data models across enterprise platforms
• Develop data curation pipelines including profiling, specification creation, cleansing, transforming, standardizing, mastering, harmonizing, validating, and aggregating data
• Monitor data quality and data integrity throughout the Context Engine environment
• Incorporate metadata management and governance processes into data ingestion, curation, and pipeline development efforts
• Evaluate and promote modern tools, architectures, and automation techniques to improve productivity and reduce manual processes
• Coordinate compliance with data governance processes and data security requirements
• Manage integrated and reusable data pipelines that improve data access and data reuse
• Ensure data provenance, security, ontology management, and data quality are consistently tracked across solutions
• Partner with Enterprise Data Engineering & Analytics teams to build and support analytics deliverables for production use
• Deliver production-ready analytics assets for key data and analytics consumers
• Support institutional data strategy initiatives through governance oversight and standards adherence
• Perform quality control reviews to ensure solutions are technically sound and aligned with best practices
• Manage and adhere to standard operating procedures established by Information Services and institutional policies
• Maintain build standards and governance sign-off processes supporting the institutional data strategy and Context Engine
• Prepare and manage implementation documentation for enhancements and new technologies
• Follow documented change control procedures and participate in change control audits when required
• Perform testing and quality validation of solutions and review the work of other analysts
• Oversee analytics system updates and new releases for assigned modules
• Ensure adherence to regulatory requirements, quality standards, and operational best practices
• Collaborate with internal and external stakeholders on system and process improvements
• Participate in after-hours application support and downtime procedures
• Train data scientists, analysts, users, and other data consumers on data pipelining and data preparation techniques
• Develop and establish training plans for Context Engine tools and related systems
• Create educational curricula in partnership with training teams and subject matter experts
• Deliver institutional, departmental, and one-on-one training related to Enterprise Data Engineering & Analytics solutions
• Coach and mentor team members across OneIS and the institution
• Provide constructive feedback, technical guidance, and knowledge transfer to less experienced team members
• Build and maintain liaison relationships with customers and OneIS teams to deliver effective technical solutions and customer service

Requirements:

• Bachelor's Degree
• 7 years relevant information technology experience
• 5 years experience with preferred degree
• EPIC Certification - Must obtain at least one Epic Data Model certification (Clinical, Access, or Revenue) issued by Epic within 180 Days
• Master's Degree in Business Analytics, Computer Science, Information Technology, Data Science, or related field
• Experience with data modeling and backend development for Epic reporting
• Cloud-based data pipeline development
• Building custom objects and data loads in Clarity and Caboodle
• Experience with Microsoft Fabric
• Building out data engineering pipelines in Fabric using Python, PySpark and related technologies
• Healthcare experience including hospital workflows