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Associate Data Engineer (Lab Medicine)

Information Technology
167777 Requisition #
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The Associate Data Engineer in the area of Data Analytics & Delivery is a role in the Enterprise Data Engineering & Analytics Department in operationalizing critical data and analytics for MD Anderson’s digital business initiatives. The Associate Data Engineer participates in business requirements gathering, components of end-to-end solution development and data analytics delivery within the Context Engine.  The Associate Data Engineer partners with other Enterprise Data Engineering & Analytics teams to assist in building components of analytics deliverables for production use by our data and analytics consumers. 

**Ideal candidates will have  Laboratory Science or Laboratory Tech experience,  Epic Beaker CP experience.  as well as SQL, Visualization tools experience**
The Associate Data Engineer also assists in planning and coordinating components of the 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 Associate Data Engineer role will require both creative and collaborative working with Principal, Senior Data Engineers and Data Engineers across the department.   

**Ideal candidates will have  Laboratory Science or Laboratory Tech experience,  Epic Beaker CP experience.  as well as SQL, Visualization tools experience**

The Laboratory Clinical Pathology (CP) area is critical to both patient care and research to improve patient care.  The Associate candidate will be self-motivated, detail-oriented and contribute to the technical projects to improve analytics and reporting for the Epic Beaker CP module.
The Context Engine program has multiple Laboratory Clinical Pathology (CP) projects in progress and this Associate position will play a role in the progress and execution of those efforts. 

Data Engineering – End-to-End Solution Delivery  
1. Participate in components of 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 of components across 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 components of 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. Incorporate components of data governance and metadata management processes into the data ingestion, curation and pipeline building efforts. 
4. Participate in data requirements gathering for various components of end-to-end analytics deliverables to ensure we are delivering what is needed, not only what is requested. 
5. Participate and implement components of 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. 
6. Perform problem solving and formulation and testing and analysis of data.  Designs queries using structure query language and NoSQL.    
7. Adhere 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. 

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

Education: Bachelor's degree.
Preferred Education: Master’s Level Degree

Certification Required : Must obtain at least one Epic Data Model certification (Clinical, Access, or Revenue) issued by Epic within 180 days of date of entry into job.

Experience Required: May substitute required education with years of related experience on a one to one basis.

Preferred Experience: Excellent communication and interpersonal skills, with the ability to work effectively with technical and non-technical stakeholders.
Detail-oriented with a strong focus on data accuracy and quality.  Ability to manage multiple projects and deadlines in a fast-paced environment.
Laboratory Science or Laboratory Tech experience.  Epic Beaker CP experience.  SQL, Visualization tools

It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html

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