The Senior Data Engineer in the area of Data Governance Support is a pivotal role in the Enterprise Data Engineering & Analytics Department in operationalizing critical data and analytics for MD Anderson’s digital business initiatives as well as planning and coordinating data governance workflows and methodologies. The Senior Data Engineer assists in managing business partner relationships with the Chief Data Office organization and data stewards to optimize information management that supports end-to-end solution delivery, data engineering and data analytics delivery within the Context Engine. The Senior Data Engineer partners with other Enterprise Data Engineering & Analytics teams to manage data and optimize analytics deliverables for production use by our key data and analytics consumers.

The Senior Data Engineer plans and coordinates information management 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 Senior Data Engineer role requires working creatively and collaboratively with IS and Institutional leaders across the enterprise. It involves clearly, precisely and consistently communicating the value of effective data governance practices and promoting better understanding of information management. The Senior Data Engineer partners closely with teams across MD Anderson, including Enterprise Development & Integration and Enterprise Data Science departments in the build out and delivery end-to-end analytic solutions through the Context Engine Framework.

Data Engineering – End-to-End Solution Delivery
1. Communicate/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. Incorporating highly integrated data governance processes that consistently tracking data provenance, security, data quality and ontology as well as through to data visualization and insights.
2. Lead/Communicate/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. Communicate/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 manage relationships with stakeholders across the organization. This includes proactively communicating with stakeholders and prioritizing work for the team.
5. Assist in driving data requirements for various end-to-end analytics deliverables to ensure we are delivering what is needed, not only what is requested.
6. Communicate/Participate and implement complex 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. Lead/Communicate/Perform complex 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. Coordinate and 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. Communicate & 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. Communicate and execute the adherence to regulatory requirements, quality standards and best practices for systems and processes, and collaborate with internal and external stakeholders.
7. Assist in leading and/or participate in after-hours application support and downtime procedures.

Educate and train
1. Coordinate, promote & train 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. Coordinate & establish 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. Coach and provide advice, guidance, encouragement, constructive feedback and transfer knowledge to less experienced team members across .

Other duties as assigned