Privacy Engineering Lead: Data Protection & PETs

Koitecc Solutions; Columbia (SC); Hybrid; USD 107,000 - 284,000; Full time

Benefits offered by this job

Medical, dental, vision

Paid time off

Retirement savings options

Wellness programs

Job summary

CVS Health is seeking a Lead Data Privacy Engineer to advance enterprise privacy engineering and data protection across structured and unstructured data. You will drive strategy, design and deployment of PETs, encryption, tokenization, and DLP, collaborating with engineering, product, legal, and compliance teams.

Responsibilities include privacy risk assessments, governance, and building scalable architectures that protect PHI and PII while enabling data-driven innovation.

Qualifications

• 7+ years in Privacy Engineering, Security Engineering, or related fields with GDPR/CCPA/HIPAA experience.
• 5+ years designing and deploying enterprise-scale data protection capabilities (encryption, tokenization, key management, DLP).
• 5+ years in cloud-native/DevSecOps environments with CI/CD and IaC.

Responsibilities

• Lead strategy and implementation of enterprise data protection and privacy engineering across structured and unstructured data.
• Design and deploy Privacy Enhancing Technologies (PETs) like encryption, tokenization, anonymization, and DLP.
• Collaborate with engineering, product, legal, compliance, and cybersecurity teams to embed privacy-by-design principles.
• Conduct privacy risk assessments, privacy impact assessments, and threat modeling to mitigate risks.

Skills

Privacy engineering

Data protection

Cybersecurity

Programming (Python/Java/Go)

Cloud-native / DevSecOps

Stakeholder leadership

Education

Bachelor's degree

Tools

Privacy Enhancing Technologies (PETs)

Encryption

Tokenization

DLP

Data classification

Job description

CVS Health is seeking a Lead Data Privacy Engineer to advance enterprise privacy engineering and data protection across structured and unstructured data. You will drive strategy, design and deployment of PETs, encryption, tokenization, and DLP, collaborating with engineering, product, legal, and compliance teams.

Responsibilities include privacy risk assessments, governance, and building scalable architectures that protect PHI and PII while enabling data-driven innovation.