• Lead the design, implementation, and optimization of enterprise Data Protection and Data Loss Prevention (DLP) solutions. • Develop and execute strategies to protect sensitive data across cloud and on-premises environments, consistent with Zero Trust architecture principles. • Recommend new features and improvements to enhance the customer’s posture on data protection, data loss prevention, and data valuation. • Collaborate with Infrastructure & Operations teams to integrate data protection capabilities within broader enterprise technology ecosystems. • Partner with the Office of the Chief Information Security Officer (OCISO) to establish frameworks, standards, and operational processes for data valuation and data classification. • Drive the creation of policies, workflows, and governance models that ensure data is adequately protected based on business value and regulatory requirements. • Serve as a subject-matter expert to federal clients on data management, data protection, and secure data handling best practices. • Provide technical leadership on enterprise data initiatives, including architecture reviews, risk assessments, and roadmap development. • Support continuous improvement by evaluating new tools, emerging technologies, and evolving compliance requirements within the data protection space. • Lead the development and implementation of enterprise data categorization and classification frameworks in support of the CDO’s Zero Trust Data Pillar, ensuring accurate identification and protection of high-value and sensitive data assets. • Design and mature data valuation models that account for data sensitivity, business criticality, lifecycle state, and usage context, enabling risk-informed decision-making and the prioritization of protection controls. • Recommend and drive enhancements to enterprise document labeling and handling processes, ensuring alignment with data classification policies, regulatory requirements, and DLP/Zero Trust enforcement mechanisms. • Translate complex data architectures, security concepts, and governance models into clear, actionable insights for mixed technical and non-technical audiences to drive adoption of enterprise data governance and protection practices. • Develop, document, and maintain data health metrics, standardized data definitions, and data governance SOPs, ensuring consistency, transparency, and operational rigor across data protection and management functions.