Data Engineer

The Data Engineer in the area of Data Analytics & Delivery is a pivotal role in the Enterprise Data Engineering & Analytics Department in operationalizing critical data and analytics for MD Anderson's digital business initiatives. The Data Engineer participates in business requirements gathering, end-to-end solution development and data analytics delivery within the Context Engine. The Data Engineer partners with other Enterprise Data Engineering & Analytics teams to assist in building analytics deliverables for production use by our data and analytics consumers.

*Ideal candidates will have experience working with Pathology and Lab Medicine, Epic Cogito certified, and have experience with SQL and developing reports in SAP Web Intelligence, PowerBI, or similar. **

Salary Range Min-$106,500, Mid-$133,000, Max-$159,500, the work schedule is remote.

Why Us?
This role offers the opportunity to lead high-impact programs that directly support UT MD Anderson's mission to eliminate cancer, while working alongside innovative leaders in technology, data, and healthcare. The Data Engineer contributes to meaningful organizational transformation while benefiting from a collaborative environment, professional development opportunities, and a strong commitment to work-life balance.
• 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.

The Data Engineer also assists in planning and coordinating data analytics delivery activities in compliance with data governance processes and data security requirements. This results in enabling faster data delivery, integrated data reuse and vastly improved time-to-solution for MD Anderson data and analytics initiatives.
The Data Engineer role requires working creatively and collaboratively with Principal and Senior Data Engineers, IS and Institutional teams across the enterprise. It involves evangelizing effective data accessibility practices and promoting better understanding of data and analytics. The Data Engineer partners with teams across MD Anderson, including Enterprise Development & Integration and Enterprise Data Science departments in the build out and delivery of end-to-end analytic solutions through the Context Engine Framework.
The Laboratory Anatomic Pathology (AP) and Clinical Pathology (CP) areas are critical to both patient care and research to improve patient care. The Data Engineer candidate will be self-motivated, detail-oriented and contribute to technical projects to improve analytics and reporting for the Epic Beaker AP and CP modules.
The Context Engine program has multiple Laboratory projects in progress and this position will play a key role in the progress and execution of those efforts.

Data Engineering - End-to-End Solution Delivery
1. Participate in End-to-end solution delivery that increases information capabilities and realizes data value across the institution. End-to-End solutions include build out of data sources and tools across the Context Engine framework by integrating data governance processes through data ingestion, ingress, egress, curation, pipeline build, data transformation and modeling steps. Build out integrated data governance processes that consistently tracking data provenance, security, data quality and ontology as well as through to data visualization and insights.
2. Participate in existing end-to-end data pipelines consisting of a series of stages through which data flows (for example, from data sources or endpoints of acquisition to integration to consumption for specific use cases).
3. Participate and incorporate data governance and metadata management processes into the data ingestion, curation and pipeline building efforts.
4. Promote Data Analytics & Delivery efforts and support relationships with stakeholders across the organization.
5. Participate in data requirements gathering for various end-to-end analytics deliverables to ensure we are delivering what is needed, not only what is requested.
6. Participate and implement data analytics deliverables, including data analysis, report requests, metrics, extracts, visualizations, projects or dashboards in a timely manner by leveraging tools and methodologies in line with the Context Engine Stra