Quick overview
Job description
Senior Systems Engineer
The Senior Systems Engineer will support data-driven decision-making for complex Department of Defense programs by applying systems engineering discipline, data analysis, and rapid visualization capabilities. This role will use Government-provided enterprise software development and analytics tools, including Advana where applicable, to develop code, applications, dashboards, and analytical products that improve access to Global Force Management Data Initiative (GFM DI) data, organizational data, and system features. The position translates operational needs into clear requirements, reliable data products, analytical models, and user-focused solutions that strengthen decision support and support the full system life cycle.
Responsibilities
- Apply systems engineering principles to analyze mission needs, coordinate technical solutions, develop requirements, and support life-cycle planning for large, complex projects.
- Data Curation - Curate, organize, and clean raw data feeds into structured, reliable datasets that are optimized for querying, reporting, and analysis.
- Establish and maintain trusted data sources that improve consistency, accuracy, and confidence in operational decision-making.
- Analytical Modeling - Develop business logic, analytical models, and statistical approaches that connect datasets and translate raw inputs into actionable trends, risks, and insights.
- Rapid Visualization - Design and deploy clean, interactive dashboards and lightweight web-based tools using platforms such as Qlik, Streamlit, or similar visualization technologies.
- Collaborate with stakeholders, analysts, engineers, and mission partners to gather requirements, validate outputs, document assumptions, and improve access to system data and features.
- Use Government-provided enterprise software development and analytics tools to conduct data analysis and develop code, applications, dashboards, and data products supporting GFM DI use cases.
- Research, assess, reconcile, and standardize disparate force element data, organizational identifiers, and related data structures used across Component systems and mission domains.
- Analyze complex system integration challenges involving the Organization Force Structure Construct, Organization Unique Identifiers, Component Org Servers, enterprise analytic platforms, and related Global Force Management tools.
- Apply analytical, statistical, or mathematical modeling approaches to support design decisions, resolve data integration issues, and generate actionable recommendations for Government stakeholders.
- Support assignment data processes and related tools, including documentation, stakeholder coordination, and training for internal users and broader Communities of Interest.
To qualify, you will need
- Master of Science degree from an accredited college or university in Systems Engineering and at least three (3) years of related experience; or
- Bachelor of Science degree in Systems Engineering and at least six (6) years of related experience; or
- Degree in another engineering discipline or operations research may be considered if the candidate has completed at least twenty-four (24) semester hours in operations research, mathematics, probability, statistics, mathematical logic, science, or other coursework requiring substantial college-level mathematics or statistics, and has significant systems engineering experience.
Clearance: Active Top Secret/SCI clearance required.
Preferred Experience: Experience using DoD analytics platforms, including Advana, and developing code, applications, dashboards, or data products that improve access to system data and features. Familiarity with GFM DI, OFSC, OUIDs, Component Org Servers, Global Force Management assignment processes, enterprise analytic platforms, Qlik, Streamlit, SQL, data modeling, dashboard development, or similar analytics and visualization tools is highly desirable. Experience supporting Planning, Intelligence, Command and Control, Logistics, Financial, or other DoD mission domains through data analysis, integration, or decision-support tools is preferred.
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