Data Engineer

Enable data-driven decision analysis for Department of Defense modernization by applying data science, machine learning, and operations research.

• Analytic consulting to support analytic workflow and product development and testing
• Promote adoption of data science methods and best practices
• Conduct applied methods projects
• Support creation of analysis-ready data
• Provide stakeholders with the analytical tools, data products, and reports needed for data-driven recommendations
• Assist analyst and technical stakeholders as well as non-analyst and non-technical stakeholders
• Analyze DoD datasets and communicate insights gained from DoD Test and Evaluation (T&E) data
• Communicate effectively at programmatic and technical levels, with support from data science teammates and software engineering and system administration teams
• Run and operate CHEETAS (and related tools)
• Demonstrate CHEETAS and related tools to stakeholders and VIPs
• Convey analysis results and adapt internally-developed tools, notebooks, and reports to meet emerging needs
• Gather use cases, requirements, gaps, and needs, and submit them as feature requests or bug reports to the CHEETAS development team
• Perform impromptu hands-on training sessions with end users and support troubleshooting as needed
• Work independently with minimal supervision and little direct tasking

Requirements

• Active or current TS/SCI Clearance required
• Degree in operations research, engineering, applied math, statistics, computer science, or information technology
• Preferred 15+ years of experience within DoD
• 10-15 years of DoD experience considered on a case-by-case basis
• Entry level candidates not considered
• At least 5 years hands-on experience in big data analytics
• At least 5 years hands-on experience with object-oriented and functional languages (e.g., 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 to inform technical choices and infrastructure configuration
• Proven experience preparing and handling large volumes of data for ETL processes
• Experience working with teams to develop and interpret results of analytic products using DoD-specific data types
• Experience installing, configuring, and using big data infrastructure (e.g., Spark, Trino, Hadoop, Hive, Neo4J, JanusGraph, HBase, MS SQL Server with Polybase, VMWare)
• Experience implementing data visualization solutions
• Experience with scripting languages Python and R to process, analyze, and visualize data
• Experience using Jupyter Notebooks and RMarkdown to create reproducible and explainable products
• Experience using interactive visualization tools (e.g., RShiny, pyShiny, Dash)
• 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
• Experience working with Windows, Linux, and containers
• Experience with SQL and querying databases; ability to work with and configure distributed storage and computing environments (e.g., 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 communicate effectively orally and in writing with customers and teammates
• Ability to present findings to 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 tool usage and novel analytic methods
• Ability to solve problems, debug, and troubleshoot under pressure and time constraints
• Self-motivated to design, develop, enhance, reengineer, or integrate software to improve data outputs for end users
• Ability to work with data scientists to develop and implement the best technical design and approach for new analytical products
• Strong analytical skills with both structured and unstructured datasets
• Excellent programming, testing, debugging, and problem-solving skills
• Experience designing, building, and maintaining new and existing data systems and solutions
• Understanding of ETL processes and experience implementing ETL processes
• Knowledge of message queuing, stream processing, and extracting value from large disparate datasets
• Knowledge of software design patterns and Agile Development methodologies required
• Knowledge of operations research, statistical and machine learning, data science, and computer science methods sufficient to select appropriate approaches for data preparation and computing architecture configuration
• Knowledge of programming concepts, data structures, and storage architecture including relational and non-relational databases, distributed computing frameworks, and modeling and simulation experimentation sufficient to select appropriate methods

Technologies

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

Location

• Onsite in Camarillo, California

Travel Requirements

• Requires 25% travel, with potential surges to 50%
• Travel to support end users at various DoD ranges and labs across the US, including Alaska and Hawaii
• When not supporting a site, may work remotely or from a nearby KBR office (if available and desired)

Working Hours

• 40 hours per week
• Standard schedule; you may be the only team member physically on-site providing support, but you will not be alone

Compensation

• $135,000 - $183,00 (California Only)
• Offered rate based on knowledge, skills, abilities, and/or experience and internal parity
• KBR may offer bonuses, commissions, or other forms of compensation 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

Trinzic Spin-Off Timing

• Trinzic is the future independent company created through the planned spin-off of KBR’s Mission Technology Solutions business, expected in January 2027
• Candidates joining KBR’s Mission Technology Solutions business before the spin-off will transition to Trinzic when separation is complete and will not need to reapply