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, manufacturing, and sustainment. Oversee the design, implementation, and maintenance of scalable data infrastructure, to include data creation/collection, storage, management, integration and analysis, and data serving through modern technology. Lead and govern the use of the Program data infrastructure and capabilities to ensure seamless data flow and traceability across engineering, supply chain, and operational systems to include functional allocated and product baseline data from our suppliers. Drive innovation and program adoption of data science, machine learning, and AI to enhance program performance. Collaborate with engineering and business leaders to align data initiatives with corporate goals, including leveraging AI, digital twins, model-based systems engineering (MBSE), and Industry 4.0 adoption. Develop and enable program data risks management process in concurrence with program risk management. Maintain knowledge of current and emerging trends and technologies in data 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. Demonstrated ability to lead cross-functional teams and ability to interface across disciplines: systems engineering, DevOps, data engineering, and IT. Strong stakeholder management skills, including presenting solutions to senior leadership. Experience in leading organizational change and ensuring successful adoption of new technologies and best practices. Experience mentoring junior engineers and fostering a culture of continuous improvement. Proven ability to 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. Proven ability to design and implement DevOps frameworks for data teams, improving operational efficiency and reducing time-to-insight. Experience in leading cloud transformation projects for legacy data systems. Demonstrated success in driving company-wide data strategy and innovation, aligning technical goals with business objectives. Ability to influence and gain buy-in from key stakeholders, ensuring alignment and successful project delivery. Expertise in data governance, data security, data modeling, and enterprise architecture frameworks. Experience in understanding, managing, and integrating business or DoD Program data across a variety of tool sets and data sources. Data Architecture experience with and understanding of data lakes, warehouses, and/or streaming platforms. Data Engineering experience with tooling, such as Apache Spark and Kafka, and orchestration tools like Apache Airflow or equivalent. Continuous Integration/Continuous Deployment experience with CI/CD tools like Jenkins or GitLab 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 and 20+ years of related experience; 18+ years of experience with a Masters; 15+ years of experience with a PhD. 10+ years of experience in data infrastructure, DevOps, and data engineering, with 3+ years in a leadership or senior technical role. Active Secret Security Clearance . Proven track record of architecting and realizing scalable, secure, and cost-effective data platforms preferably utilizing cloud-based platforms. Demonstrated experience in leading large-scale projects from conception to deployment, managing multidisciplinary teams, and driving success through strategic vision and strong leadership. Proven track record of providing data driven insights at scale through data engineering, data integration and data science practices. Strong communication and presentation skills for collaborating with data scientists, engineers, and leadership stakeholders. Ability to travel up to 25%. Master's degree or Ph.D. in data engineering, data science, computer science, cloud computing, or a related field. Active Top-Secret Security Clearance . 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.