Qualis is seeking an experienced Modeling and Simulation (M&S) Data Manager to oversee the architecture, governance, and security of simulation-derived datasets within our defense programs. In this role, you will lead data administration for high-fidelity synthetic environments, digital twins, and predictive military models. Your primary focus will be ensuring that all M&S data structures comply with DoD enterprise standards, remain highly secure, and seamlessly interface with High-Performance Computing (HPC) environments to support joint-force warfighter readiness and system testing. Essential DutiesDoD Data Strategy Enforcement: Implement and manage simulation data architecture aligned with Pentagon VAULTIS guidelines, ensuring datasets are Visible, Accessible, Understandable, Linked, Trustworthy, Interoperable, and Secure. VV&A Data Pedigree: Document, archive, and manage the data pedigree required for strict Verification, Validation, and Accreditation (VV&A) under DoDI 5000.61.Classified Data Lifecycle: Oversee data extraction, transformation, and loading (ETL) pipelines for massive synthetic and live-virtual-constructive (LVC) environments across secure enclaves. Database & Repository Administration: Build and optimize relational and non-relational database structures (e.g., PostgreSQL, SQL Server) to host complex mission profiles, threat environments, and sensor simulations. Cross-Agency Collaboration: Partner with defense engineers, data scientists, and military stakeholders to establish clean, automated data pipelines for downstream analytical tools.
Required Qualifications:
Security Clearance & Citizenship: Must possess an active U.S. Secret Security Clearance and maintain eligibility for upgrade. U.S. Citizenship is mandatory.
Education:
Bachelor's degree in Computer Science, Data Science, Information Technology, Engineering, or a related quantitative field.
Experience:
Minimum of 3 to 5 years of experience managing technical data structures, database architecture, or data engineering within a federal, defense, or highly regulated industrial environment. Core Technical Proficiency: Advanced proficiency in SQL database administration and query design. Proven experience using Python or R for data cleaning, curation, and pipeline automation. Data Architecture: Strong understanding of Entity-Relationship (ER) mapping, metadata management, and physical storage optimization for large datasets.
Preferred Qualifications:
DoD M&S Standards: Direct experience with military distributed simulation protocols, including HLA (High Level Architecture), DIS (Distributed Interactive Simulation), and TENA (Test and Training Enabling Architecture).Cybersecurity Baseline: Possession of a DoD 8570/8140 IAT Level II certification (such as CompTIA Security+ CE) or higher. Defense M&S Systems: Familiarity with standard DoD simulation ecosystems (e.g., OneSAF, AFSIM, Joint Simulation System (JCS), or MATLAB/Simulink).Data Modeling Software: Mastery of enterprise data modeling platforms like SAP Power Designer, erwin Data Modeler, or Microsoft Visio. Configuration Management: Robust experience in version-controlling data variations, baselines, and simulation builds via Git or similar defense configuration tools. Professional Credentials: Certifications such as Certified Data Management Professional (CDMP) or platform-specific cloud/database credentials. Qualis LLC has a comprehensive benefits package based on employment type, location, and applicable agreements that includes: Health, dental, and vision insurance 401(k) match Paid time off and Holidays Paid time off and Holidays Educational, professional development and certification reimbursement. Tax-saving options Disability and Life Insurance Qualis LLC is committed to hiring and retaining a diverse and talented workforce who can contribute to the mission and vision of the Company. Our employees are our greatest asset, and we promote a positive work environment, teamwork, professional growth, innovation, community involvement, flexible scheduling and a family-friendly work environment.
