Spacecraft Software and Data Visualization Systems Engineer

KBR, Inc.•El Segundo, CA

1d•$150,200 - $187,700•Onsite

About The Position

KBR's National Security Solutions team provides high-end engineering and advanced technology solutions to customers in the intelligence and national security communities. This position offers the opportunity to have a profound impact on the country’s most critical role – protecting national security. KBR is seeking a motivated and experienced spacecraft or spacecraft subsystem SME to join their team in El Segundo, CA. KBR is the prime contractor on the Military Satellite Communications (MILSATCOM) Systems Engineering, Integration and Test (MSEIT) contract. The MSEIT effort provides leading-edge Systems Engineering & Integration (SE&I) for the United States Space Force’s (USSF) Space Systems Command (SSC). This role involves acquiring state-of-the-art Military and Commercial Satellite Communications (SATCOM) systems, providing global secure, survivable, and protected communications for the nation’s warfighters. The ideal candidate will thrive in a highly collaborative work environment of small teams, using modern tools and methodologies to tackle the challenges of integrating complex space and ground communications systems.

Requirements

An active Secret Clearance is required for this position
Bachelor’s degree in technical field, such as engineering, mathematics, physics, software or computer science
10+ years of experience in data visualization, analytics, software engineering, or related technical fields.
5+ years of experience in space systems (SATCOM, NASA, etc.)
Demonstrated experience developing dashboards and visual analytics solutions.
Experience working with large, complex datasets in operational or engineering environments.
Experience with Python, SQL, and data analytics frameworks.
Proficiency with one or more visualization platforms: Power BI, Tableau, Grafana, Plotly/Dash, D3.js, Similar enterprise visualization tools
Understanding of machine learning concepts, model evaluation, and predictive analytics.
Experience working with cloud-based or distributed analytics environments.
Demonstrated organizational management capability with ability to handle competing priorities
Strong interpersonal skills, communication (oral and written), and presentation skills
Demonstrated ability to clearly articulate ideas, recommendations and options to customers, senior leaders, and stakeholders
Proficient in Microsoft Office (Outlook, Word, Excel, PowerPoint)

Nice To Haves

TS/SCI clearance
Master’s degree in technical field, such as engineering, mathematics, physics, software or computer science
Experience in Military, DoW, or Intelligence Community space
Experience with MILSATCOM, such as ESS, AEHF, EPS, PTES, PTS, WGS, and FAB-T terminal programs
Experience in space systems engineering at the unit, subsystem, spacecraft or space vehicle levels
Knowledge and experience in Jira and Confluence
Experience integrating or interacting with Statistical and Machine Learning (SML) models and AI-driven analytics.
Certifications in Systems Engineering (INCOSE ESEP, CSEP)

Responsibilities

Provide the technical leadership and assessment for the ESS Program Office in the prime contractor delivery of the space vehicle
Lead the trades for unit and subsystem designs if necessary, integration and testing of both the spacecraft bus and space vehicle (after the payload had been integrated)
Ensure the technical design and interfaces within the space vehicle, along with the ground and terminal segments
Support all component and unit test programs, including space qualification testing ensuring survivability in the space environments. Develop test documentations, e.g. test plan and reports as necessary
Support the space vehicle test program, ensuring survivability in the space environments. Develop test documentations, e.g. test plan and reports as necessary
Build and maintain strong, collaborative relationships with various government customer organizations, contractors, and FFRDC teammates
Design visual interfaces that expose model predictions, confidence intervals, explainability metrics, and performance indicators.
Develop user-facing analytics that enable engineers and operators to interact with, evaluate, and refine AI/ML-driven insights.
Support validation, interpretation, and communication of machine learning outcomes to technical and non-technical stakeholders.
Collaborate with data scientists and machine learning engineers to operationalize outputs from Statistical and Machine Learning (SML) models.