Within the Enterprise Data Engineering & Analytics Department, the
Principal Data Engineer plays a pivotal role in operationalizing critical data engineering and analytics initiatives that support digital business objectives, enterprise data accessibility, and advanced analytics delivery.
The Principal Data Engineer leads the design, development, optimization, and operationalization of enterprise data solutions across the Context Engine framework. The Principal Data Engineer partners with technology, governance, analytics, and business stakeholders to build integrated data pipelines, enable reusable data assets, and accelerate time-to-solution across UT MD Anderson while ensuring compliance with governance, security, and quality standards.
The
ideal candidate possesses a preferred Master's Degree in Business Analytics, Computer Science, Information Technology, Data Science, or a related field, along with experience in data modeling and backend development for Epic reporting, cloud-based data pipeline development, building custom objects and data loads in Clarity and Caboodle, Microsoft Fabric, Python, PySpark, and healthcare environments including hospital workflows. The successful candidate demonstrates strong leadership, solution architecture expertise, and the ability to educate and mentor stakeholders on modern data engineering practices.
Minimum $146,500 - Midpoint $183,000 - Maximum $219,500
Work Location: Remote 100% within Texas only
ResponsibilitiesData Engineering - End-to-End Solution Delivery• 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
Data Governance, Analytics & Quality• 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
Standards, Testing & System Maintenance• 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
Education, Training & Mentorship• 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
OneIS Commitments
• Provide innovative, quality, and sustainable information technology solutions and services
• Promote integrity, trust, respect, support, and honesty with customers and colleagues
• Build productive, collaborative, and trusted partnerships across the institution
• Demonstrate a commitment to excellence and continuous improvement
• Achieve outcomes that exceed expectations for quality, usability, and value
• Perform other duties as assigned
EDUCATION- Required: Bachelor's Degree
- Preferred: Master's Degree Business Analytics, Computer Science, Information Technology, Data Science, or related.
WORK EXPERIENCE- Required: 7 years Relevant information technology experience. or
- Required: 5 years Experience with preferred degree.
- May substitute required education with years of related experience on a one to one basis.
- Preferred: Experience with data modeling and back end for Epic reporting, cloud base data pipeline and development, building custom objects and custom data loads/load packages in Clarity and Caboodle, experience with Microsoft Fabric and building out data engineering pipelines in Fabric using Python, PySpark and related technologies, and healthcare experience including hospital workflows.
LICENSES AND CERTIFICATIONS- Required: EPIC - EPIC Certification Must obtain at least one Epic Data Model certification (Clinical, Access, or Revenue) issued by Epic. within 180 Days
The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
