Epic Data Engineer Analytics

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 be Epic certified****

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.

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 Strategy.
7. Perform problem solving and formulation and testing and analysis of data.  Designs queries using structure query language and NoSQL.   
8. Collaborate with other data engineers on integration efforts. Promote and ensure institutional data management strategies.

Standards, Testing & System Maintenance  
1. Adhere to standard operating procedures set by IS division as well as all MDA policies and maintain build standards (data steward / governance oversight sign off) for support of MDA Institutional data strategy including Context Engine.
2. Participate in documentation preparation as needed for the implementation of enhancements or new technology.
3. Adhere to documented change control processes and may perform change control audits.
4. Perform quality control and testing and review the build of other analysts to ensure that solutions are technically sound.
5. Assist in overseeing analytics system updates/new releases for assigned modules.
6. Adhere to regulatory requirements, quality standards and best practices for systems and processes, and collaborate with internal and external stakeholders.
7. Participate in after-hours application support and downtime procedures.

Educate and train   
1. Participate in training counterparts, such as data scientists, data analysts, end users or any data consumers, in data pipelining and preparation techniques, which make it easier for them to integrate and consume the data they need for their own use cases.
2. Assist in establishing training plans for various systems in the Context Engine Tools suite and develop curricula in partnership with the MDA Training team and EDEA system experts.
3. Provide institutional, department and one-on-one training on EDEA deliverables.
4. Assist in supporting liaison relationships with customers and OneIS to provide effective technical solutions and customer service.

OneIS   
1. To provide innovative, quality, and sustainable IT solutions and services. Our success is driven by our people through Integrity and Trust, Partnership, and Quality.
2. Promotes trust, respect, support, and honestly with customers and each other.
3. Commits to being a good partner focused on building productive, collaborative, and trusting relationships with our customers and each other.
4. Models a commitment to excellence and strives to continually improve. Achieves desired outcomes, usability, and value that exceed expectations of others and our own.

Other duties as assigned