Data Analyst

Great Hill Solutions is part of the Seneca Nation Group (SNG) portfolio of companies. SNG is the federal government contracting business wholly owned by the Seneca Nation. SNG meets mission-critical needs of federal civilian, defense, and intelligence community customers across a variety of domains. The SNG portfolio receives shared services support from its parent company Seneca Holdings and is comprised of multiple companies that participate in the Small Business Administration 8(a) program. To learn more visit www.senecanationgroup.com and follow us on LinkedIn. 

The Seneca Nation Group companies offer competitive compensation and a strong benefits package including comprehensive medical and dental care, matching 401K, paid time off, flexible spending accounts, disability coverage, and other benefits that help provide financial protection for you and your family. We pride ourselves on our collaborative work environment and culture which embraces our mission of providing financial and non-financial benefits back to the members of the Seneca Nation. 

Great Hill is seeking a Data Analyst in the National Capital Region. The candidate will provide direct support to the Defense Security Cooperation Agency (DSCA) Chief Data Officer and Artificial Intelligence Officer (CDAO) to track and manage use case requirements for Security Cooperation (SC) data and identify opportunities to improve workflow, individual productivity, and time-to-market for data and analytic products. The candidate will support the implementation of DSCA data policy and processes to ensure policies are resulting in demonstrated business value. They should also recognize that there are two evolving overlapping data architectures: The emerging Case Execution Modernization Initiative (CEMI) federated data architecture that includes local reporting capabilities and transactional interfaces, and the enterprise reporting architecture currently in Advana that consumes data from legacy and modernized case development, execution, financial, supply chain, procurement, and acquisition systems.  Additionally, the candidate will support the DSCA CDAO on issues related to data management and cross-functional business data integration.   

Roles and Responsibilities include, but are not limited to: 

• Centrally manage use case requirements and identify opportunities to improve workflow, individual productivity (for a persona) and time-to-market for analytic products. Establish a clearinghouse where common requirements are pooled and allocated to projects to optimize developer resources.  

• Evolve the DSCA Data Governance policy and processes to emphasize the data pipelines and analytic products being developed on the Advana platform as part of their oversight role. Shift the focus from policy coordination to ensuring the policies are resulting in demonstrated business value. Recognize that there are two evolving overlapping data architectures: The emerging Case Execution Modernization Initiative (CEMI) federated data architecture that shall include local reporting capabilities and transactional interfaces, and the enterprise reporting architecture in Advana that shall consume data from the modernized case execution systems. 

• Support the requirements gathering, use of rapid prototyping employed to explore Business Intelligence (BI) opportunities using existing data, while also identifying gaps in the data needed to fully address business needs.  

• Proactively engage in the Advana platform technical roadmap to understand, influence, and adopt full lifecycle tools for designing, operating, managing, and optimizing a modern data integration environment. The goal is to increase developer productivity and reduce time-to-market for data products.  

• Rationalize and prioritize enterprise data management and analytic requirements considering both architectures with a balancing of resources commensurate with DSCA strategic initiatives.  

• Work within a Data Integration Center of Excellence (COE) to facilitate collaboration among data stewards to improve the quality and resiliency of the data ingest and integration pipelines. The