Data Engineer

Data Engineer role supporting DoD modernization through data science, machine learning, and operations research focused on testing and evaluation.

Responsibilities

• Provide analytic consulting services that support analytic workflow and product development and testing
• Promote adoption of data science methods and best practices across analytic workflows
• Conduct applied methods projects and support creation of analysis-ready data
• Help stakeholders use the analytical tools, data products, and reports needed to make data-driven recommendations
• Directly assist both analyst and technical stakeholders and non-analyst and non-technical stakeholders with analysis of DoD datasets
• Demonstrate insights from DoD Test and Evaluation (T&E) data to stakeholders and VIPs, including “art of the possible” outcomes
• Communicate effectively at programmatic and technical levels, collaborating with data science team members and partnering with software engineering and system administration teams
• Run and operate CHEETAS and related tools
• Demonstrate CHEETAS and other tools to stakeholders and VIPs, convey analysis results, and adapt internally developed tools, notebooks, and reports to emerging needs
• Collect stakeholder use cases, requirements, gaps, and needs for larger development items and submit them as feature requests or bug reports to the CHEETAS development team
• Conduct impromptu hands-on training sessions with end users and troubleshoot problems as needed
• Work independently with minimal 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
• Preferred: 15+ years of experience within DoD
• 10-15 years of DoD experience considered case-by-case
• Entry level candidates will not be considered
• 5 years of hands-on experience in big data analytics
• 5 years of hands-on experience with object-oriented and functional languages (e.g., Python, R, C++, C#, Java, Scala, etc.)
• Experience dealing with imperfections in data
• Competency across software engineering concepts, programming, statistical analysis, data mining algorithms, machine learning, and modeling to inform technical choices and infrastructure configuration
• Proven analytical skills preparing and handling large volumes of data for ETL processes
• Experience developing and interpreting analytic products with 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 with scripting languages Python and R to process, analyze, and visualize data
• Experience with Jupyter Notebooks and RMarkdown to create reproducible and explainable products
• Experience with interactive visualization tools (RShiny, pyShiny, Dash)
• Experience generating and presenting reports, visualizations, and findings to customers
• Experience building and optimizing big 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/configuring distributed storage and computing environments (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 present findings to large technical and non-technical groups
• Ability to create documentation and repeatable procedures to support 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 applications to improve data outputs for end users
• Ability to work with data scientists to develop and implement technical designs and approaches 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 data systems and solutions
• Understanding of ETL processes and experience implementing ETL
• Knowledge of message queuing, stream processing, and 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 to select appropriate methods 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

Required 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; Camarillo, California

Travel Requirements

• 25% travel required; potential surge 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, remote work or work from a nearby KBR office may be available and desired

Working Hours

• Standard hours (40 scheduled weekly hours)
• You may be the only team member physically on-site providing support, and you will not be alone

Compensation

• Basic compensation: $135,000 - $183,00 (California Only)
• Offered rate based on knowledge, skills, abilities, and/or experience, and internal parity
• Additional compensation: 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 expected to become an independent company through a planned spin-off of KBR’s Mission Technology Solutions business in January 2027
• Candidates who join KBR’s Mission Technology Solutions business before the spin-off will transition to Trinzic when separation is complete and will not need to reapply