Data Engineer - Enterprise Data Engineering & Analytics

This role is a pivotal position within the Enterprise Data Engineering & Analytics Department, supporting the design, build, and operationalization of integrated data pipelines and analytics solutions that enable MD Anderson's digital business initiatives. The Data Engineer works across the Context Engine framework to deliver end-to-end data engineering solutions while partnering closely with Enterprise Data Engineering & Analytics teams and other institutional stakeholders. The role contributes to the mission of MD Anderson Cancer Center, a leading institution focused on cancer care, research, education, and prevention, by advancing enterprise analytics capabilities and ensuring secure, governed, and reusable data assets that accelerate insights and improve time-to-solution.

Responsibilities

• Participate in end-to-end solution delivery to increase information capabilities and realize data value across the institution.
• Build and test end-to-end data pipelines across ingestion, curation, transformation, modeling, and consumption within the Context Engine framework.
• Integrate data governance processes across data provenance, security, data quality, 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.
• Build data curation pipelines including profiling, specification creation, cleansing, transforming, standardizing, mastering, harmonizing, validating, and aggregating data.
• Monitor and support data quality across the Context Engine.
• Incorporate repeatable solution designs and data models to support reuse and scalability.
• Promote effective data management practices and understanding of analytics across the enterprise.
• Adhere to IS division standard operating procedures and all MD Anderson policies.
• Maintain build standards and governance oversight sign-off aligned with institutional data strategy.
• Participate in documentation preparation for enhancements or new technology.
• Perform quality control, testing, and peer review of analytics builds.
• Support system updates, releases, change control processes, and after-hours support as required.
• Train data scientists, analysts, end users, and data consumers on data pipelining and preparation techniques.
• Assist in establishing training plans and curricula for Context Engine tools.
• Provide institutional, department, and one-on-one training on EDEA deliverables.
• Support liaison relationships with customers and OneIS partners to deliver effective technical solutions.
• Explore and promote modern tools, techniques, and architectures to automate data preparation and integration tasks.
• Improve productivity by reducing manual and error-prone processes.
• Model OneIS values through integrity, partnership, quality, and continuous improvement.

Requirements

• Bachelor’s degree in computer science, business analytics, information technology, data science, or related field. Preferred: Master’s degree in a related field.
• Required: 2 years of 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.
• Preferred: 3-5 years creating data pipelines in a healthcare research environment.
• Experience building and maintaining analytical reports and dashboards.
• Problem-solving skills and ability to translate business/clinical requirements into reliable data models, analytics, and reporting.
• Cloud data management solutions experience (e.g., Foundry, Fabric).
• Data pipeline & ETL development: hands-on experience designing, building, and maintaining pipelines using Python or Spark.
• Hands-on use of Large Language Models (LLMs) in real-world projects, such as integrating generative AI solutions into applications, workflows, or analytics platforms. Familiarity with prompt engineering, model evaluation, and responsible AI practices.
• Experience collaborating with cross-functional teams to deploy and scale LLM-powered features is highly desirable.
• Preferred certifications: Epic Cogito, Clarity, Caboodle, Clinical Data Model, etc.
• Required: Must obtain at least one Epic Data Model certification (Clinical, Access, or Revenue) issued by Epic within 180 days of hire.
• Must pass pre-employment skills test as required and administered by Human Resources.

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, plus 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 and employer-paid life and reduced salary protection programs.

Pay

Salary range based on a 40-hour work week: $106,500 – $159,500 (Midpoint: $133,000).

Schedule

Full-time, exempt position. Work week: Days.

Work location: Houston, Texas or surrounding area preferred. Remote work within Texas only.