Data Engineer - Enterprise Data Engineering & Analytics

Within the Enterprise Data Engineering & Analytics Department, the Data Engineer plays a critical role in operationalizing enterprise data engineering and analytics initiatives that support digital business priorities. The department is responsible for building scalable data pipelines, advancing analytics capabilities, and enabling trusted data access through the Context Engine framework.
The Data Engineer supports end-to-end solution delivery, data governance, analytics enablement, and data pipeline operationalization. The Data Engineer also promotes effective data management practices that improve data reuse, accelerate time-to-solution, and enhance institutional analytics capabilities.
The ideal candidate has a preferred Master's Degree in Business Analytics, Computer Science, Information Technology, Data Science, or a related field, along with experience using Palantir Foundry and Microsoft Fabric. Candidates with Epic certification in at least one Clinical, Access, or Revenue module are highly desirable. Individuals should demonstrate strong collaboration skills and an interest in data engineering, analytics, data governance, and enterprise-scale data solutions.
Minimum - $106,500, Midpoint $133,000 – Maximum $159,500
Work Location: Remote 100% within Texas

Why Us?
At UT MD Anderson, the Data Engineer contributes directly to the organization's mission by enabling access to trusted, governed, and high-quality data that supports patient care, research, education, and operational excellence. This position offers opportunities to work with modern data platforms, collaborate with enterprise technology and analytics teams, and build innovative solutions while maintaining work-life balance through a fully remote Texas-based work arrangement.
• Employer-paid medical coverage starting day one for employees working 30+ hours/week, plus optional group dental, vision, life, AD&D, and disability insurance.
• Accruals for PTO and Extended Illness Bank, plus paid holidays, wellness, childcare, and other leave options.
• Tuition Assistance Program after six months of service and access to extensive wellness, fitness, and employee resource groups.
• Defined-benefit pension through the Teachers Retirement System, voluntary retirement plans, and employer-paid life and reduced salary protection programs.
Responsibilities
Data Engineering – End-to-End Solution Delivery
• Participate in end-to-end solution delivery that increases information capabilities and realizes data value across the institution.
• Build and support data sources and tools across the Context Engine framework through ingestion, ingress, egress, curation, transformation, modeling, and integration activities.
• Support data governance processes that track data provenance, security, data quality, and ontology throughout the data lifecycle.
• Participate in planning, architecture, analysis, design, and implementation of enterprise data pipelines and solutions.
• Partner with Information Systems, Data Offices, Data Governance teams, and other stakeholders to manage institutional data efficiently.
• Support existing end-to-end data pipelines from acquisition and integration through analytics consumption.
• Build data curation pipelines that include profiling, specification creation, cleansing, transformation, standardization, mastering, harmonization, validation, aggregation, and monitoring.
• Incorporate repeatable solution designs and data models into enterprise data solutions.
• Integrate metadata management and governance processes into ingestion, curation, and pipeline development activities.
• Explore and promote modern tools, technologies, and architectures that automate repeatable data preparation and integration activities.
Data Governance, Analytics & Collaboration
• Create, improve, and operationalize integrated and reusable data pipelines.
• Enable faster access to trusted data and maximize data reuse across the enterprise.
• Partner with Enterprise Development & Integration and Enterprise Data Science teams to deliver analytics solutions.
• Adhere to effective data management practices and promote understanding of data and analytics.
• Collaborate creatively with Principal and Senior Data Engineers and enterprise technology teams on solution delivery initiatives.
Standards, Testing & System Maintenance
• Adhere to Information Systems standard operating procedures, institutional policies, and data stewardship requirements.
• Support institutional data strategy initiatives, including Context Engine objectives.
• Participate in development and maintenance of technical documentation for enhancements and new technologies.
• Follow documented change control procedures and participate in change control audits when required.
• Perform quality control testing and review solutions to ensure technical soundness.
• Assist with analytics platform updates and new-release implementation activities.
• Adhere to regulatory requirements, quality standards, and industry best practices.
• Collaborate with internal and external stakeholders to maintain effective processes and systems.
• Participate in after-hours application support and downtime procedures.
Education, Training & Customer Support
• Train data scientists, data analysts, end users, and other data consumers on data pipelining and preparation techniques.
• Assist with development of training plans for Context Engine tools and related systems.
• Partner with training teams and subject matter experts to develop educational curricula.
• Provide institutional, departmental, and individual training on Enterprise Data Engineering & Analytics deliverables.
• Support customer relationships and collaborate with OneIS to deliver effective technical solutions and service.
OneIS Commitments
• Provide innovative, high-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 organization.
• Demonstrate continuous improvement and commitment to delivering outcomes that exceed expectations.
Requirements