[Remote] Data Engineer - Data & AL Solution

Note: The job is a remote job and is open to candidates in USA. UT MD Anderson Cancer Center is hiring a Data Engineer to advance enterprise data engineering and analytics initiatives supporting institutional priorities. The role develops and supports scalable data pipelines, trusted data access, governance practices, analytics solutions, and the Context Engine framework, while collaborating with technical and business stakeholders.

Responsibilities

• 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 existing end-to-end data pipelines from acquisition and integration through analytics consumption
• Participate in planning, architecture, analysis, design, and implementation of enterprise data pipelines and solutions
• Incorporate repeatable solution designs and data models into enterprise data solutions
• Explore and promote modern tools, technologies, and architectures that automate repeatable data preparation and integration activities
• Support data governance processes that track data provenance, security, data quality, and ontology throughout the data lifecycle
• Integrate metadata management and governance processes into ingestion, curation, and pipeline development activities
• Build data curation pipelines that include profiling, specification creation, cleansing, transformation, standardization, mastering, harmonization, validation, aggregation, and monitoring
• Create, improve, and operationalize integrated and reusable data pipelines
• Enable faster access to trusted data and maximize data reuse across the enterprise
• Adhere to effective data management practices and promote understanding of data and analytics
• Partner with Information Systems, Data Offices, Data Governance teams, and other stakeholders to manage institutional data efficiently
• Partner with Enterprise Development & Integration and Enterprise Data Science teams to deliver analytics solutions
• Collaborate creatively with Principal and Senior Data Engineers and enterprise technology teams on solution delivery initiatives
• Support institutional data strategy initiatives, including Context Engine objectives
• Support customer relationships and collaborate with OneIS to deliver effective technical solutions and service
• Adhere to Information Systems standard operating procedures, institutional policies, and data stewardship requirements
• 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
• 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 OneIS commitments by delivering 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
• Perform other duties as assigned

Skills

• Bachelor's Degree
• 2 years Clinical, relevant healthcare information technology, or relevant business experience
• With preferred degree, no experience required
• May substitute required education with years of related experience on a one to one basis
• One Epic Data Model certification must be maintained
• EPIC - EPIC Certification Must obtain at least one Epic Data Model certification (Clinical, Access, or Revenue) issued by Epic. within 180 Days
• EPIC - Epic Accredited Must obtain at least one Epic Data Model accreditation (Clinical, Access, or Revenue) issued by Epic. within 180 Days
• Master's Degree Business Analytics, Computer Science, Information Technology, Data Science, or related
• Experience with a modern data and analytics platform (Microsoft Fabric, Azure, Power BI, Palantir Foundry)
• At least 2 years of hands-on work experience with AI/ML model and feature engineering processes
• Proficiency in SQL
• Must understand how ontologies are structured and implementing semantic layers

Benefits

• Employer-paid medical coverage starting day one for employees working 30+ hours/week
• Optional group dental, vision, life, AD&D, and disability insurance
• Accruals for PTO and Extended Illness Bank
• Paid holidays, wellness, childcare, and other leave options
• Tuition Assistance Program after six months of service
• Access to extensive wellness, fitness, and employee resource groups
• Defined-benefit pension through the Teachers Retirement System
• Voluntary retirement plans
• Employer-paid life and reduced salary protection programs
• Remote work within Texas only, with onsite presence a few times a year for key organizational/department meetings or key project/internal customer meetings; other onsite opportunities may be optional
• Referral bonus
• Relocation assistance
• Educational opportunities
• Individual and team recognition

Company Overview

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