Über
Why Join Us?
Innovative Projects: KBR’s work is at the forefront of engineering, logistics, operations, science, program management, mission IT and cybersecurity solutions.
Collaborative Environment: Be part of a dynamic team that thrives on collaboration and innovation, fostering a supportive and intellectually stimulating workplace.
Impactful Work: Your contributions will be pivotal in designing and optimizing defense systems that ensure national security and shape the future of space defense.
Key Responsibilities As a Data Engineer, you will be a critical part of the team that is responsible for enabling the development of data‑driven decision analysis products through the innovative application, and promotion, of novel methods from data science, machine learning, and operations research to provide robust and flexible testing and evaluation capabilities to support DoD modernization.
Analytic Experience: Provide analytic consulting services, support analytic workflow and product development and testing, promote user adoption of methods and best practices from data science, conduct applied methods projects, and support the creation of analysis‑ready data.
Onsite Support: Serve as the face of the CHEETAS Team, ensuring stakeholders have the analytical tools, data products and reports they need to make insightful recommendations based on your data‑driven analysis.
Stakeholder Assistance: Directly assist both analyst/technical and non‑analyst/non‑technical stakeholders with the analysis of DoD datasets and demonstrate the 'art of the possible' to stakeholders and VIPs with insights from your analysis of DoD Test and Evaluation data.
Communication: Effectively communicate at both a programmatic and technical level, both in person and through documentation.
Technical Support: Run and operate CHEETAS (and other tools); demonstrate these tools to stakeholders & VIPs; convey analysis results; adapt internally‑developed tools, notebooks and reports to meet emerging needs; gather use cases, requirements, gaps and needs from stakeholders and provide that information as feature requests or bug reports to the CHEETAS development team; and perform impromptu hands‑on training sessions with end users and troubleshoot problems from within closed networks without internet access.
Independent Work: Self‑motivated and capable of working independently with little supervision or direct tasking.
Work Environment
Location: Onsite; Honolulu, HI
Travel Requirements: 25 % travel with potential surge to 50 % to support end users located at various DoD ranges and labs across the US (including Alaska and Hawaii). When not supporting a site, this position can work remotely or from a nearby KBR office (if available and desired).
Working Hours: Standard; the employee may be the only team member physically on‑site but will have support from the distributed team.
Basic Qualifications
Security Clearance: Active or current TS/SCI clearance is required.
Education: A degree in operations research, engineering, applied math, statistics, computer science or information technology. Preferred 15+ years of experience within DoD; candidates with 10–15 years may be considered on a case‑by‑case basis. Entry level candidates will not be considered.
Technical Experience: Five (5) years of hands‑on experience in big data analytics and five (5) years in object‑oriented and functional languages (Python, R, C++, C#, Java, Scala, etc.).
Data Experience: Competency in software engineering, computer programming, statistical analysis, data mining algorithms, machine learning, and modeling sufficient to inform technical choices and infrastructure configuration.
Data Analytics: Proven analytical skills and experience in preparing and handling large volumes of data for ETL processes; working with teams in the development and interpretation of analytic products with DoD‑specific data types.
Big Data Infrastructure: Experience installing, configuring and using big data infrastructure (Spark, Trino, Hadoop, Hive, Neo4J, JanusGraph, HBase, MS SQL Server with Polybase, VMWare, etc.) and implementing data visualization solutions.
Qualifications Required
Experience using scripting languages (Python and R) to process, analyze and visualize data.
Experience using notebooks (Jupyter Notebooks and RMarkdown) to create reproducible and explainable products.
Experience using interactive visualization tools (RShiny, pyShiny, Dash) to create interactive analytics.
Experience generating and presenting reports, visualizations and findings to customers.
Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
Experience cleaning and preparing time series and geospatial data for analysis.
Experience working with Windows, Linux, and containers.
Experience querying databases using SQL and working with distributed storage and computing environments to conduct analysis (Spark, Trino, Hadoop, Hive, Neo4J, JanusGraph, MongoDB, Accumulo, HBase).
Experience working with code repositories in a collaborative team.
Ability to make insightful recommendations based on data‑driven analysis and customer interactions.
Ability to effectively communicate orally and in writing with customers and teammates.
Ability to present findings in front of large technical and non‑technical groups.
Ability to create documentation and repeatable procedures to enable reproducible research.
Ability to create training and educational content for novice end users on the use of tools and novel analytic methods.
Problem‑solving, debugging, and troubleshooting skills under pressure and time constraints.
Self‑motivation to design, develop, enhance, re‑engineer or integrate software applications to improve the quality of data outputs available for end users.
Use of Agile Development methodologies and software design patterns is required.
Knowledge of methods from operations research, statistical and machine learning, data science, and computer science sufficient to select appropriate methods.
Knowledge of computer programming concepts, data structures and storage architecture, including relational and non‑relational databases, distributed computing frameworks, and modeling and simulation experimentation to select appropriate methods.
Understanding of ETL processes and experience implementing them.
Knowledge of message queuing, stream processing and extracting value from large disparate datasets.
Scheduled Weekly Hours 40
Basic Compensation $119,900 – $179,800
Additional Compensation KBR may offer bonuses, commissions, or other forms of compensation to certain job titles or levels, per internal policy or contractual designation. Additional compensation may be in the form of sign‑on bonus, relocation benefits, short‑term incentives, long‑term incentives, or discretionary payments for exceptional performance.
KBR is an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity or expression, age, national origin, veteran status, genetic information, union status and/or beliefs, or any other characteristic protected by federal, state, or local law.
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Sprachkenntnisse
- English
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