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Data Engineer

KBR

Salary not specified
Aug 28, 2025
Honolulu, HI, USA • Nellis AFB, NV, USA
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KBR's National Security Solutions team is seeking a Data Engineer to support the TRMC BDKM team in revolutionizing how analysis is performed across the Department of Defense. The role involves enabling the development of data-driven decision analysis products through the application of novel methods from data science, machine learning, and operations research to provide robust and flexible testing and evaluation capabilities for DoD modernization.

Requirements

  • Previous experience must include five (5) years of hands-on experience in big data analytics, five (5) years of hands-on experience with object-oriented and functional languages (e.g., Python, R, C++, C, Java, Scala, etc.).
  • Experience in dealing with imperfections in data. Experience should demonstrate competency in key concepts from software engineering, computer programming, statistical analysis, data mining algorithms, machine learning, and modeling sufficient to inform technical choices and infrastructure configuration.
  • Proven analytical skills and experience in preparing and handling large volumes of data for ETL processes. Experience should include working with teams in the development and interpretation the results of analytic products with DoD specific data types.
  • Experience in the installation, configuration, and use of big data infrastructure (Spark, Trino, Hadoop, Hive, Neo4J, JanusGraph, HBase, MS SQL Server with Polybase, VMWare as examples). Experience in implementing Data Visualization solutions.
  • 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 querying databases using SQL and working with and configuring distributed storage and computing environments to conduct analysis (Spark, Trino, Hadoop, Hive, Neo4J, JanusGraph, MongoDB, Accumulo, HBase as examples).

Responsibilities

  • Candidate will be a part of the technical team responsible for providing analytic consulting services, supporting analytic workflow and product development and testing, promoting the user adoption of methods and best practices from data science, conducting applied methods projects, and supporting the creation of analysis-ready data.
  • Candidate will be the face of the CHEETAS Team and will be responsible for ensuring stakeholders have the analytical tools, data products and reports they need to make insightful recommendations based on your data driven analysis.
  • Candidate will directly assisting both analyst / technical and non-analyst / non-technical stakeholders with the analysis of DoD datasets and demonstrating the 'art of the possible' to the stakeholders and VIPs with insights gained from your analysis of DoD Test and Evaluation (T&E) data.
  • Candidate will be responsible for running and operating CHEETAS (and other tools); demonstrating these tools to stakeholders & VIPs; conveying analysis results; adapting internally-developed tools, notebooks and reports to meet emerging needs; gathering use cases, requirements, gaps and needs from stakeholders and for larger development items providing that information as feature requests or bug reports to the CHEETAS development team; and performing impromptu hands-on training sessions with end users and potentially troubleshooting problems from within closed networks without internet access (with support from distributed team members).
  • Experience using scripting languages (Python and R) to process, analyze and visualize data.
  • Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
  • Experience designing, building, and maintaining both new and existing data systems and solutions

Other

  • Active or current TS/SCI Clearance is required
  • Must effectively communicate at both a programmatic and technical level.
  • Candidate must be self-motivated and capable of working independently with little supervision / direct tasking.
  • Ability to make insightful recommendations based on data driven analysis and customer interactions.
  • Ability to effectively communicate both orally and in writing with customers and teammates.