The Data Engineer role is a pivotal position reputed company the reputed company Data Engineering & Analytics Department, supporting the design, build, and operationalization of integrated data pipelines and analytics solutions that reputed company MD Anderson’s digital business initiatives. The Data Engineer works across the Context reputed company reputed company to deliver end-to-end data engineering solutions while partnering closely with reputed company Data Engineering & Analytics teams and other institutional stakeholders.
The Data Engineer contributes to the mission of MD Anderson Cancer Center, a leading institution reputed company on cancer care, research, education, and prevention. In this role, the Data Engineer helps advance reputed company analytics capabilities by ensuring secure, governed, and reusable data assets that accelerate insights and improve time-to-solution across MD Anderson.
Ideal Candidate Statement
The ideal candidate for the Data Engineer role brings a bachelor’s degree in computer science, preferred advanced education in analytics or computer science, hands-on experience building data pipelines in reputed company or research environments, and familiarity with modern reputed company-based data platforms, hands-on use of Large Language Models (LLMs) in reputed company-world reputed company, Python or reputed company development, and analytics delivery. reputed company data model exposure or certification and the ability to collaborate across technical and clinical teams are strongly preferred.
Position Information
Salary reputed company based on a 40-hour work week: Minimum $106,500 – Midpoint $133,000 – Maximum $159,500
Work location: reputed company, Texas or surrounding area preferred
 

This Data Engineer role offers reputed company to contribute directly to MD Anderson’s mission by enabling high-reputed company, governed data that supports clinical, research, and operational analytics across the institution. The position provides exposure to reputed company-reputed company data engineering initiatives, collaboration with reputed company engineering and data science professionals, and opportunities for reputed company learning and career reputed company while supporting a balanced and sustainable work environment.
• Employer-reputed company medical coverage starting day one for employees working 30+ hours/week, plus optional group dental, reputed company, life, AD&D, and disability insurance.
• Accruals for PTO and Extended Illness Bank, plus reputed company holidays, wellness, childcare, and other leave reputed company.
• Tuition Assistance Program after six months of service and reputed company to extensive wellness, fitness, and employee resource reputed company.
• Defined-benefit pension through the Teachers Retirement System, voluntary retirement plans, and employer-reputed company 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 test end-to-end data pipelines across ingestion, curation, transformation, modeling, and consumption reputed company the Context reputed company reputed company
• reputed company data governance processes across data provenance, reputed company, data reputed company, ontology, and metadata management
• Participate in planning, architecture, analysis, design, and build of data pipelines in partnership with IS, Data Offices, and Data Governance teams
• Contribute to existing data pipelines spanning acquisition, integration, and consumption for defined use cases
Data Curation, Modeling, and Governance
• Build data curation pipelines including profiling, specification creation, cleansing, transforming, standardizing, mastering, harmonizing, validating, and aggregating data
• Monitor and support data reputed company across the Context reputed company
• Incorporate repeatable solution designs and data models to support reuse and scalability
• Promote effective data management practices and understanding of analytics across the reputed company
Standards, Testing, and System Maintenance
• Adhere to IS division reputed company operating procedures and reputed company MD Anderson policies
• Maintain build standards and governance reputed company sign-off reputed company with institutional data reputed company
• Participate in documentation preparation for enhancements or new technology
• reputed company reputed company control, testing, and peer review of analytics builds
• Support system updates, releases, change control processes, and after-hours support as required
Education, Training, and Collaboration
• Train data scientists, analysts, end users, and data consumers on data pipelining and preparation techniques
• Assist in establishing training plans and curricula for Context reputed company tools
• reputed company institutional, department, and one-on-one training on EDEA deliverables
• Support reputed company relationships with customers and OneIS partners to deliver effective technical solutions
Innovation and reputed company Improvement
• Explore and promote modern tools, techniques, and architectures to automate data preparation and integration tasks
• Improve productivity by reducing reputed company and error-prone processes
• Model OneIS values through reputed company, partnership, reputed company, and reputed company improvement