Sentinel - Staff Systems Data Architect - 15907

Develop and execute a comprehensive data strategy, aligned with the organization's goals, and focuses on digital engineering, digital thread, and advanced analytics across weapon system design for initial development through sustainment. Oversee the design, implementation, and maintenance of scalable data infrastructure, to include data creation/collection, storage, management, integration and analysis, and data serving. Collaborate with engineering and business leaders to align data initiatives with program goals. Develop and enable program data risks management process in concurrence with program risk management. Maintain knowledge of current and emerging Industry and DoD trends and technologies in data frameworks, management and analytics and ensure proper utilization where applicable. Mentor and build a high-performing data team, fostering a culture of technical excellence and innovation. Serve as a thought leader, representing the company at industry forums, conferences, and with government and commercial partners. Display strong stakeholder management skills, including presenting solutions to senior leadership. Leading organizational change and ensuring successful adoption of new technologies and best practices. Mentor junior engineers and fostering a culture of continuous improvement. Build and lead high-performing teams, including recruitment, performance management, and professional development. Ability to strategically allocate resources and manage budgets to optimize team performance and deliver value-driven results. Design and implement DevOps frameworks for data teams, improving operational efficiency and reducing time-to-insight. Drive company-wide data strategy and innovation, aligning technical goals with business objectives. Influence and gain buy-in from key stakeholders, ensuring alignment and successful project delivery. Manage data governance, data security, data modeling, and enterprise architecture frameworks. Provide experience in understanding, managing, and integrating business or DoD Program data across a variety of tool sets and data sources. Data Architecture development with and understanding of data lakes, warehouses, and/or streaming platforms. Technical Skills and Core Competencies: Data Engineering experience with Architecture frameworks such as FACE, GCIA, EAF, FAF,OCSF Data Engineering experience with modeling languages such as AADL, SysML, and UML and tooling modeling environments, processes, and tools such as ACVIP, CAMEO, Rational, OSATE, CAMET, and CVIT. Continuous Integration/Continuous Deployment experience with CI/CD tools like Git tailored for data pipelines. Cloud Expertise experience and/or knowledge in cloud platforms like AWS or Azure. Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field with 12 years of experience; or Master's degree with 10 years of experience; or PhD with 8 years of experience Must be a US Citizen with an active U.S. Government DoD Secret security clearance at time of application with an investigation completed within the last 6 years Must have the ability to obtain Special Access Program (SAP) 4+ years of experience in data infrastructure, DevOps, and data engineering, with 2+ years in a leadership or senior technical role. 3 years of experience architecting and realizing scalable, secure, and cost-effective network platforms 3 years of demonstrated experience in leading large-scale projects from conception to deployment, managing multidisciplinary teams, and driving success through strategic vision and strong leadership. Travel up to 25% Master's degree or Ph.D. in data engineering, data science, computer science, cloud computing, or a related field. Active TS/SCI or TS with SCI eligibility at time of application. Relevant certifications such as AWS Certified Solutions Architect (Professional), AWS Certified Data Analytics Specialty, Azure Data Engineer Associate, or Google Professional Data Engineer. MLOps Expertise, Observability Tools, Data Versioning, and Containerization for deploying data engineering workflows. Expertise in cloud security best practices, including IAM, encryption, and compliance with frameworks like NIST or FedRAMP. Knowledge of advanced networking concepts such as VPC peering, VPNs, and load balancing for data-heavy applications.