Principal Data Engineer

Principal Data Engineer

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

UT MD Anderson offers the opportunity to lead transformative enterprise data initiatives that directly support innovation in healthcare, research, and operational excellence. This role provides exposure to advanced data engineering technologies, enterprise-scale analytics, collaborative partnerships across the institution, and opportunities to develop leadership expertise while maintaining the flexibility of a fully remote Texas-based work environment.

Responsibilities include:

• Data Engineering – End-to-End Solution Delivery
• Data Governance, Analytics & Quality
• Standards, Testing & System Maintenance
• Education, Training & Mentorship
• OneIS Commitments

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.

It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state, or local laws unless such distinction is required by law.