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 COE ensures data quality is measured, authoritative data is identified, and data models, labels, and standards are aligned for frictionless data sharing and algorithm development. The COE facilitates involvement by data stewards in the active management of Advana pipelines and development of data sets that benefit DSCA. COE participants are involved in the defining and applying the Advana DataOps playbook to DSCA data pipelines.  

• Develop data source ingest pipelines that are resilient, instrumented, and status is automatically reported to data stewards and Advana developer/sustainment teams for action if required.  

• Provide Data quality (DQ) measures and improvements in accordance with defined criteria for Silver and Gold data zones. DQ is to be reported through managed and enhanced self-service tools (e.g., Great Expectations python library) and reported to data stewards and Advana developer/sustainment teams.  

• Make data easy to find and well managed with quality, communicated in the Federated Catalog tool Collibra. Data sources are to be auto cataloged and integrated with data dictionaries metadata that provide understanding through exposure of data descriptions and business rules that facilitate data integration Lineage for curated data sets is fully documented to provide understanding of providence and pedigree.  

• Ensure that Data is curated based on requirements and designed with reusability in mind. Only Gold data sets are offered to share with DoD writ large, with off-platform sharing accomplished using the platform OpenAPI feature. Data sharing agreements track usage in the Data Usage registry to alert downstream data consumers of issues.  

• In the interest of DSCA, coordinate work across various Advana lines of businesses (Acquisition, Procurement, Supply Chain, and Finance) to continually improve the ability to link SC data with other domain data. Manage the DSCA data sources inventory and associated metadata lifecycle using the Advana Federated Catalog. Coordinate with Data Stewards to capture, store, integrate and deliver (publish) metadata accordance with DSCA policy requirements. Develop supporting templates and tools to streamline the upload and maintenance of metadata capture and storage.  

• Work with the Advana catalog team to integrate SCA metadata with other Advana data assets to include mapping of data dictionaries to authoritative sources, mapping of data sets to data dictionaries, and creation of data linage views that trace data from source to point of consumption. Support reporting of metadata using the Advana tools including the status of SCA data source pipelines and their data quality (scorecard for coverage, completeness, and timeliness), and use of SCA data sets by Advana dashboard applications.  

• Support training of Data Stewards regarding metadata responsibilities and use of catalog tools. Maintain the DSCA metadata metamodel and requirements and use it to measure the progress towards implementation in Advana in terms of scope and features.  
  
• Provide expertise, advisory, and leadership to:  
  -Leverage AI and Game Changer for enhanced natural language processing (NLP), curating unstructured data for more business value.  
  -Leverage ML with Advanced Analytics to deliver the Financial Management Improvement Initiative (FMII) forecasting products shall become more accurate over time as the models learn from experience.  
  -Develop automated Financial Improvement and Audit Readiness (FIAR) controls to support DSCA audit requirements and provide ease of evidence to support audits and address findings.  
  -Develop DSCA Advanced Analytics roadmap and strategy to deliver insights to leadership at all levels.  
  -Establish DSCA Robotics Process Automation program to continuously elicit new requirements to improve operational processes and develop and deploy automations. Deploy self-service desktop analytics via an available tool that shall be available to DSCA customers with access to only Gold tables.  

Basic Qualifications: 

• Must have a minimum of 8 years of experience in data management. 

• Must have a minimum of 3 years of experience with SQL. 

• Must have a Bachelor's degree in Computer Science, Information Systems, Engineering, Business, or a scientific or technical discipline.  

• Must have active SECRET clearance (an Interim Secret is acceptable). 

• Ability to lead joint initiatives to foster collaborative, cooperative and constructive working relationships, resolve conflicts and negotiate with others, with strong cultural awareness. Results oriented, willingness to prioritize workload and drive operations to completion. 

• Excellent oral communication skills and good writing skills. Must have competent writing skills, and the ability to work independently in Microsoft Office, specifically Visio, PowerPoint, Word, and Excel.   

Desired Skills: 

• Experience with Python.  

• Understanding of Procurement Lifecycle. 

• Experience with enterprise data tools like Iquery, databricks, Erwin data modeler, etc.