Senior Data Visualization Engineer

KBR, Inc.•El Segundo, CA

11d•$116,000 - $158,600

About The Position

KBR is seeking highly motivated Senior Data Visualization Engineer to design and develop advanced data visualization solutions supporting satellite communications (SATCOM), network operations, and engineering analysis. This role will transform complex operational, engineering, and machine learning outputs into intuitive dashboards, reports, and analytical applications that enable executive, engineering, and operational stakeholders to aid senior leaders make data-driven decisions. The ideal candidate combines strong data visualization and software development skills with deep SATCOM domain expertise and the ability to integrate and interact with Statistical/Machine Learning (SML) models. This position requires close collaboration with systems engineers, data scientists, network engineers, software developers, and program leadership. The MILSATCOM Systems Engineering, Integration, and Test (MSEIT) effort provides leading edge Systems Engineering & Integration (SE&I) for the US Space Force’s Space Systems Center (SSC). We support the Space Force’s acquisition of state of the art satellite communications systems, providing global secure, survivable, and protected communications for our nation’s warfighters. We seek technical individuals who will thrive in a highly collaborative work environment of small teams, using the most modern tools and methodologies to tackle the challenges of integrating complex space and ground communications systems.

Requirements

Ability to obtain a Secret clearance is required to be considered for this position
Bachelor’s degree in engineering, computer science, or similar technical field
5+ years of experience in data visualization, analytics, software engineering, or related technical fields.
Demonstrated experience developing dashboards and visual analytics solutions.
Experience working with large, complex datasets in operational or engineering environments.
Demonstrated organizational management capability with ability to handle competing priorities
Proficiency with one or more visualization platforms: Power BI, Tableau, Grafana, Plotly/Dash, D3.js, Similar enterprise visualization tools
Experience with Python, SQL, and data analytics frameworks.
Knowledge of digital engineering and Model-Based Systems Engineering (MBSE) environments.
Understanding of machine learning concepts, model evaluation, and predictive analytics.
Experience working with cloud-based or distributed analytics environments.
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

Nice To Haves

Active DoW Secret clearance or higher
3+ years demonstrated experience with MILSATCOM, such as AEHF, EPS, PTES, PTS, WGS, and FAB-T terminal programs
Experience working with military or DoD civilian clients
Experience with ground and airborne systems, such as terminals and networks
Certifications in Systems Engineering (INCOSE ESEP, CSEP)
Knowledge and experience in Jira and Confluence
Experience integrating or interacting with Statistical and Machine Learning (SML) models and AI-driven analytics.

Responsibilities

Develop interactive dashboards, visual analytics platforms, and automated reporting solutions using modern visualization technologies.
Translate complex engineering, telemetry, network performance, and operational datasets into actionable visual insights.
Design visualizations that support real-time monitoring, trend analysis, anomaly detection, predictive analytics, and executive reporting.
Establish visualization standards, best practices, and governance across programs and teams.
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.
Work across multidisciplinary engineering teams to define visualization requirements and analytic workflows.
Guide architecture decisions for data pipelines and visualization environments.
Mentor junior engineers and analysts in visualization and analytics best practices.
Support customer demonstrations, reviews, and technical presentations.