Data Engineer

Trinzic is supporting mission-focused data and analytics work through a KBR spin-off, delivering data-driven decision analysis products for the Department of Defense. In this onsite role in Honolulu, you will help build and operate analytics capabilities and ETL/data pipelines, while directly supporting stakeholders who rely on CHEETAS tools and analytic workflows to interpret DoD Test and Evaluation data.

Working as part of the CHEETAS team, you will serve as a hands-on technical resource for both analyst and non-analyst stakeholders, translating findings into actionable insights and helping teams adopt methods and best practices.

Responsibilities

• Provide analytic consulting services to support analytic workflow and product development and testing, promoting adoption of data science methods and best practices.
• Conduct applied methods projects and support the creation of analysis-ready data.
• Serve as the face of the CHEETAS Team to ensure stakeholders have the analytical tools, data products, and reports needed for data driven recommendations.
• Assist both technical and non-technical stakeholders with analysis of DoD datasets and demonstrate the “art of the possible” using insights from DoD Test and Evaluation (T&E) data.
• Communicate effectively at both programmatic and technical levels.
• Run and operate CHEETAS (and other tools), demonstrate them to stakeholders and VIPs, convey analysis results, and adapt internally developed tools, notebooks, and reports to meet emerging needs.
• Collect use cases, requirements, gaps, and needs from stakeholders, and submit details as feature requests or bug reports to the CHEETAS development team.
• Perform impromptu hands-on training sessions with end users and troubleshoot problems.
• Work independently with little supervision or direct tasking.

Requirements

• Active or current TS/SCI Clearance is required.
• Degree in operations research, engineering, applied math, statistics, computer science, or information technology.
• Entry level candidates will not be considered.
• At least five (5) years of hands-on experience in big data analytics.
• At least five (5) years of hands-on experience with object-oriented and functional languages (examples include Python, R, C++, C#, Java, Scala).
• Experience dealing with imperfections in data.
• Competency in software engineering and programming, statistical analysis, data mining algorithms, machine learning, and modeling sufficient to inform technical choices and infrastructure configuration.
• Proven analytical skills preparing and handling large volumes of data for ETL processes.
• Experience working with teams developing and interpreting analytic products using DoD specific data types.
• Experience installing, configuring, and using big data infrastructure (examples include Spark, Trino, Hadoop, Hive, Neo4J, JanusGraph, HBase, MS SQL Server with Polybase, VMWare).
• Experience implementing data visualization solutions.
• 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) for interactive analytics.
• Experience generating and presenting reports, visualizations, and findings to customers.
• Experience building and optimizing big data data pipelines, architectures, and datasets.
• 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 and configuring distributed storage and computing environments for analysis (examples include 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 speak and 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 tools and novel analytic methods.
• Ability to solve problems, debug, and troubleshoot while under pressure and time constraints is required.
• Self-motivation to design, develop, enhance, reengineer, or integrate software applications to improve data outputs for end users.
• Ability to work with data scientists to develop and implement best technical design and approach for new analytical products.
• Strong analytical skills across structured and unstructured datasets.
• Excellent programming, testing, debugging, and problem-solving skills.
• Experience designing, building, and maintaining both new and existing data systems and solutions.
• Understanding of ETL processes and experience implementing ETL processes.
• Knowledge of message queuing and stream processing, including extracting value from large disparate datasets.
• Knowledge of software design patterns and Agile Development methodologies is required.
• Knowledge of operations research, statistical and machine learning, data science, and computer science methods sufficient to select approaches for data preparation and computing architecture configuration.
• Knowledge of computer programming concepts, data structures, and storage architecture, including relational and non-relational databases, distributed computing frameworks, and modeling and simulation experimentation sufficient to select approaches for data preparation and computing architecture configuration.
• 15+ years of experience within DoD is preferred; 10-15 years may be considered case-by-case.

Technology Focus

• Python, R, C++, C#, Java, Scala
• Jupyter Notebooks, RMarkdown, RShiny, pyShiny, Dash
• SQL
• Spark, Trino, Hadoop, Hive
• Neo4J, JanusGraph, HBase
• MS SQL Server, Polybase, VMWare
• MongoDB, Accumulo
• ETL, CHEETAS
• Windows, Linux, containers
• Message queuing, stream processing
• Agile Development

Location and Work Environment

• Onsite: Honolulu, HI
• Travel: 25% required, with potential surge to 50% to support end users across DoD ranges & labs in the US (including Alaska and Hawaii).
• When not supporting a site, the role can work remotely or from a nearby KBR office if available and desired.
• Working hours: Standard, with the expectation that you may be the only team member physically on-site providing support, though you will not be alone.

Compensation

• Basic compensation: USD 119,900 - 179,000 per year
• Salary range is for the Hawaii area only.
• Offered rate is based on the selected candidate’s knowledge, skills, abilities, and/or experience, and internal parity.

Benefits

• KBR may offer bonuses, commissions, or other forms of compensation for certain job titles or levels per internal policy or contractual designation.
• Additional compensation may include sign on bonus, relocation benefits, short term incentives, long term incentives, or discretionary payments for exceptional performance.