Data Scientist (W2 Only)

The Data Infrastructure & Data Modeling Engineer will support the design, development, and maintenance of enterprise data infrastructure supporting Combat Mission Systems operations. This role is responsible for creating and maintaining scalable data models, optimizing data pipelines, and ensuring secure, reliable, and accessible data across complex systems and large datasets. The ideal candidate will have strong experience with data modeling, data architecture, analytics infrastructure, and cross-functional collaboration within engineering and technical environments. Key Responsibilities

• Design and implement conceptual, logical, and physical data models to accurately represent organizational data
• Collaborate with business analysts, architects, developers, and stakeholders to gather requirements and align data models with business and technical needs
• Maintain centralized data dictionaries, metadata repositories, and enterprise data standards
• Optimize data infrastructure performance through tuning, redundancy reduction, and improved scalability and reusability
• Design and support data integration solutions across multiple systems and platforms
• Perform reverse engineering of existing databases and data structures when required
• Develop and maintain documentation, naming conventions, coding standards, and data governance practices
• Ensure data is stored securely, efficiently, and remains accessible for analytics, reporting, and operational usage
• Implement data validation, quality control, and data integrity processes
• Optimize data pipelines for performance, scalability, and reliability
• Support data scientists, analysts, and engineering teams by ensuring infrastructure meets operational and analytical requirements
• Troubleshoot data infrastructure issues and perform ongoing system monitoring and maintenance
• Support configuration control, change impact analysis, and enterprise data architecture management
• Identify and manage Authoritative Sources of Truth (ASOT) databases and related data integrations
• Support data replication and transformation activities within Midas and AWS cloud environments using Power BI and related technologies

Do you have experience in Visual Basic?, Do you have a Bachelor’s degree?, * Bachelors degree in Data Management, Data Science, Mathematics, Statistics, or related field

• Minimum 6 years of relevant experience
• Experience designing and maintaining enterprise data models and data infrastructure
• Strong understanding of data warehousing concepts and data architecture principles
• Experience with entity-relationship diagrams (ERDs), dimensional modeling, normalization, and metadata repositories
• Proficiency with:
• Power BI
• SQL
• AWS / AWS Redshift
• Oracle
• SSAS
• MS Excel
• Visual Basic
• MATLAB / Simulink
• Mathcad
• MagicDraw
• Midas
• Alation
• Dataiku
• Experience with cloud-based data services such as AWS or Azure
• Familiarity with big data technologies including Hadoop or Spark
• Background in data governance and data quality methodologies
• Strong analytical and problem-solving abilities
• Excellent written and verbal communication skills
• Experience working in Agile or Scrum environments
• Ability to collaborate effectively with both technical and non-technical stakeholders, * Masters degree in Mathematics, Statistics, Engineering, Business, Applied Sciences, Management Information Systems, or related discipline
• 10+ years of relevant experience
• Experience with structured problem-solving methodologies
• Experience supporting engineering or manufacturing organizations
• Experience working directly with development teams
• Familiarity with Agile performance metrics and reporting
• 1+ years of Scrum or Agile management experience
• Knowledge of technical systems and requirements related to combat vehicles

Work Environment

• Highly collaborative environment supporting engineering, analytics, and enterprise data initiatives
• Focus on enterprise-scale data architecture, governance, and digital transformation
• Combinat
• ion of technical implementation, stakeholder collaboration, and process improvement activities