Data Engineer - Enterprise Data Engineering & Analytics

What you’ll do

Support Enterprise Data Engineering & Analytics (EDEA) within Customer Support by participating in end-to-end data solution delivery through the Context Engine Framework. You will contribute to analytics operations, customer support enablement, standards/testing, system maintenance, and training and engagement activities.

• Participate in end-to-end delivery that increases institutional information capabilities and realizes data value across the organization.
• Support data ingestion, ingress, egress, curation, pipeline development, data transformation, and data modeling within the Context Engine Framework.
• Integrate data governance processes across the data lifecycle, including data provenance, security, data quality, and ontology.
• Support data visualization and insight generation through enterprise analytics solutions.
• Join the team support model for analytics security, change control, application database maintenance, and customer queue monitoring.
• Participate in scrum ceremonies and sprint activities supporting product owners and solution delivery initiatives.
• Support work intake activities and EDEA requests aligned with organizational strategy and framework standards.
• Handle routine reporting requests and support analytics consumers across the institution.
• Troubleshoot incidents, break-fixes, and production issues in coordination with system technical support teams.
• Respond to customer requests with clear procedures, expectations, delivery timelines, and status updates.
• Participate in after-hours application support and downtime procedures; assist with issue resolution to maintain service continuity.
• Adhere to IS division standard operating procedures and institutional policies supporting data governance and Context Engine standards.
• Assist with documentation for enhancements, implementations, and new technologies; follow documented change control processes and participate in change control audits as needed.
• Perform quality control testing and review peer solutions for technical accuracy and quality.
• Assist with analytics system updates and new release activities for assigned modules.
• Support regulatory compliance, quality standards, best practices, and stakeholder collaboration efforts.
• Train data scientists, data analysts, end users, and data consumers on data pipelining and data preparation techniques, including development of training plans, curricula, and materials in partnership with the training team and system experts.
• Provide institutional, departmental, and one-on-one training on EDEA deliverables.
• Support liaison relationships with customers and OneIS to provide effective technical solutions and service.
• Promote trust, respect, support, integrity, and honesty with customers and colleagues; build productive, collaborative partnerships.
• Perform other duties as assigned.

Required qualifications

• Bachelor’s Degree
• 2 years of clinical, relevant healthcare information technology, or relevant business experience
• With a preferred degree, no experience required
• Education substitution: may substitute required education with years of related experience on a one-to-one basis
• EPIC certification requirement: must obtain at least one Epic Data Model certification (Clinical, Access, or Revenue) issued by Epic within 180 days

Preferred qualifications

• Experience with end-to-end solution delivery, including build-out of EMR system data sources
• Experience communicating and problem solving issues with doctors, managers, and/or leaders
• Experience building reports in EMR
• Preferred certifications: Caboodle, Clarity, Ambulatory, Cadence, Cogito, Inpatient
• Preferred education: Master’s Degree in Business Analytics, Computer Science, Information Technology, Data Science, or related

Tools and technologies

• Context Engine Framework
• Context Engine Tools suite
• EMR
• Epic
• OneIS
• Caboodle
• Clarity
• Ambulatory
• Cadence
• Cogito
• Inpatient

Location and employment details

• Houston, TX (remote)
• Remote 100% within Texas
• Employment status: Full-Time
• Employee status: Regular
• Work week: Days
• Fund type: Hard
• Pivotal position: Yes
• Referral bonus available: Yes
• Relocation assistance available: Yes

Why UT MD Anderson

As a Data Engineer, you contribute directly to advancing data-driven healthcare, analytics innovation, and enterprise-wide decision-making. The role supports collaboration with multidisciplinary teams, modern data platform work, and the opportunity to grow technical and leadership capabilities while working remotely within Texas.