CVS Health is increasing its investment in digital, data, analytics and technology, with Signify Health playing a key role. We are seeking a dynamic Security Engineer - Data Discovery to contribute to a pioneering initiative at CVS Health's state-of-the-art offices at Bonham Quay.
About the Opportunity
This is an exciting opportunity to be part of a business transforming healthcare in the United States by enhancing customer experiences, convenience, and personalization.
About CVS Health
CVS Health is focused on driving business agility and growth through technology, data, digital and experiential innovations. Our goal is to be 'Digital First, Technology Forward and Data Driven', not just an aspiration, but a prerequisite for accelerated growth.
Career Purpose and Values
At CVS Health, every employee shares a single purpose: Bringing our heart to every moment of your health. This purpose guides our commitment to delivering enhanced human-centric healthcare in a rapidly changing world.
Key Responsibilities
* Design, configure, and implement enterprise-wide data discovery, classification, and labeling capabilities across hybrid on-prem and cloud environments.
* Create and tune data detection rules and engines to scan, tag, and categorize structured, semi-structured, and unstructured data based on regulatory and business requirements.
* Prioritize discovery and classification features based on business priorities and customer needs.
* Integrate data discovery tools with workflow, backup/restore, event logging, and applicable SaaS platforms.
Requirements
* 5+ years of technical data security experience building and managing sophisticated tools and processes in support of cybersecurity protection and strategy initiatives.
* 3+ years of hands-on experience with engineering and administration of data discovery, labeling, and classification platforms.
* Demonstrated experience working with a wide range of internal and external stakeholders.
Estimated Salary: €80,000 - €110,000 per annum
The ideal candidate will have proven success implementing innovative data discovery, classification, and labeling technologies and processes for risk-driven data protection. Experience with security solutions for data loss prevention, encryption, proxy, cloud data security, structured data security, and insider risk is preferred. Industry certifications and knowledge of data security and privacy regulatory compliance frameworks and standards are also highly valued.