Senior Cloud Data Security Engineer - Data Loss Prevention; DLP

We're building a world of health around every individual - shaping a more connected, convenient and compassionate health experience. At CVS Health, you'll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger - helping to simplify health care one person, one family and one community at a time.

CVS Health is seeking a Senior Cloud Data Security Engineer
- Data Loss Prevention (DLP) to help safeguard the sensitive data assets of one of the nation’s largest healthcare, pharmacy, and retail organizations. The Senior Cloud Data Security Engineer
- Data Loss Prevention (DLP) serves as a senior member of the Data Protection Team and is responsible for designing, implementing, and advancing enterprise-wide data protection capabilities that secure Data in Motion (DIM), Data in Use (DIU), and cloud-hosted data across a highly complex and regulated environment. The Senior Cloud Data Security Engineer
- Data Loss Prevention (DLP) will lead the development and maturation of strategic DLP programs spanning cloud, endpoint, email, network, SaaS, and AI/ML ecosystems while ensuring alignment with business objectives, regulatory requirements, and evolving cyber threats.

The Senior Cloud Data Security Engineer
- Data Loss Prevention (DLP) partners closely with Cybersecurity, Infrastructure, Cloud Engineering, Data Engineering, AI/ML, Enterprise Architecture, Privacy, Compliance, and business teams to deliver scalable and effective data protection solutions. The Senior Cloud Data Security Engineer
- Data Loss Prevention (DLP) is responsible for preventing unauthorized disclosure, misuse, loss, or exfiltration of sensitive information, including PHI, PII, PCI, and proprietary CVS Health data. This position will drive data classification and labeling initiatives, enhance visibility into data movement across enterprise platforms, and build automated detection and response capabilities that improve security outcomes while minimizing operational friction.

As CVS Health accelerates adoption of cloud services, artificial intelligence, and machine learning technologies, the Senior Cloud Data Security Engineer
- Data Loss Prevention (DLP) will play a critical role in securing AI-enabled business processes, identifying and mitigating risks associated with shadow AI usage, and implementing controls that protect sensitive information throughout AI/ML pipelines, model training environments, and generative AI platforms. Success in the Senior Cloud Data Security Engineer
- Data Loss Prevention (DLP) position requires deep expertise in enterprise DLP technologies, cloud security architectures, data governance, automation, and regulatory compliance, along with the ability to influence technical strategy, lead complex initiatives, and serve as a trusted subject matter expert for enterprise data protection.

• Design, implement, and continuously mature enterprise Data Loss Prevention (DLP) strategies, policies, and controls across cloud, endpoint, email, network, SaaS, and collaboration platforms to protect sensitive data from unauthorized access, disclosure, misuse, and exfiltration.
• Lead the end-to-end DLP program lifecycle, including data classification and labeling, policy development, rule tuning, incident management, investigations, root cause analysis, remediation, and continuous improvement of data protection capabilities governing PHI, PII, PCI, and proprietary information.
• Architect and enhance cloud data protection capabilities across AWS, Azure, GCP, and hybrid environments utilizing technologies and frameworks such as Microsoft Purview, CASB, CNAPP, CSPM, SASE, DSPM, Conditional Access, and Zero Trust architectures.
• Design, implement, and enforce data protection controls for AI/ML platforms, generative AI solutions, Large Language Models (LLMs), AI agents, MLOps pipelines, and shadow AI use cases to prevent unauthorized ingestion, exposure, retention, or transmission of sensitive and regulated data.
• Develop dashboards, metrics, key risk…