Spacecraft Software and Data Visualization Systems Engineer

KBR•El Segundo, CA

3d•Onsite

About The Position

KBR's National Security Solutions team is seeking a motivated and experienced spacecraft or spacecraft subsystem SME to join their team in El Segundo, CA. As the prime contractor on the Military Satellite Communications (MILSATCOM) Systems Engineering, Integration and Test (MSEIT) contract, KBR provides high-end engineering and advanced technology solutions to customers in the intelligence and national security communities. This role offers the opportunity to work on innovative projects at the forefront of engineering, logistics, operations, science, program management, mission IT, and cybersecurity solutions. The position is within a dynamic and collaborative team environment, using modern tools and methodologies to tackle complex space and ground communications systems integration challenges. The work has a profound impact on protecting national security and shaping the future of space defense.

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.