Data Engineer

KBR•Honolulu, HI

45d•$119,900 - $179,000•Onsite

About The Position

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. The 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. The 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. The candidate will 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 the stakeholders and VIPs with insights gained from your analysis of DoD Test and Evaluation (T&E) data. You must effectively communicate at both a programmatic and technical level. Although you potentially may be the only team member physically on-site supporting you will not be alone. You will have support from other data science team members as well as the software engineering and system administration teams. The 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). The candidate must be self-motivated and capable of working independently with little supervision / direct tasking.

Requirements

Active or current TS/SCI Clearance is required
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 of DoD experience will be considered on a case-by-case basis)
Entry level candidates will not be considered
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
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 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 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 working with Windows, Linux, and containers
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)
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 both 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 solve problems, debug, and troubleshoot while under pressure and time constraints
Strong analytical skills related to working with both structured and unstructured datasets
Excellent programming, testing, debugging, and problem-solving skills
Understanding of ETL processes, how they function and experience implementing ETL processes required
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 methods from operations research, statistical and machine learning, data science, and computer science is sufficient to select appropriate methods to enable data preparation and computing architecture configuration to implement these approaches
Knowledge of computer programming concepts, data structures and storage architecture, to include relational and non-relational databases, distributed computing frameworks, and modeling and simulation experimentation sufficient to select appropriate methods to enable data preparation and computing architecture configuration to implement these approaches

Nice To Haves

Travel of 25% with potential surge to 50% to support end users located at various DoD ranges & labs located across the US (including Alaska and Hawaii)

Responsibilities

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
Supporting the creation of analysis-ready data
Ensuring stakeholders have the analytical tools, data products and reports they need
Directly assisting stakeholders with the analysis of DoD datasets
Demonstrating the 'art of the possible' to stakeholders and VIPs
Effectively communicating at both a programmatic and technical level
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
Providing information as feature requests or bug reports to the CHEETAS development team
Performing impromptu hands-on training sessions with end users
Troubleshooting problems from within closed networks without internet access
Working independently with little supervision / direct tasking
Designing, developing, enhancing, reengineering or integrating software applications to improve the quality of data outputs available for end users
Working closely with data scientists to develop and subsequently implement the best technical design and approach for new analytical products
Building and optimizing ‘big data’ data pipelines, architectures and data sets
Cleaning and preparing time series and geospatial data for analysis
Querying databases using SQL
Working with and configuring distributed storage and computing environments to conduct analysis
Generating and presenting reports, visualizations and findings to customers
Creating documentation and repeatable procedures to enable reproducible research
Creating training and educational content for novice end users on the use of tools and novel analytic methods
Solving problems, debugging, and troubleshooting while under pressure and time constraints
Designing, building, and maintaining both new and existing data systems and solutions