Embed Privacy by Design: Strengthen and operationalize Privacy by Design across systems, integrations, pipelines, and applications for B2B and B2C products and services
Investigate & Remediate Incidents: Analyze privacy and security incidents, perform root cause analysis, and drive remediation
Conduct Risk Assessments: Assist in privacy impact assessments for new products or data uses and risk reviews
Optimize Privacy Controls: Design and implement controls for data classification, access management, encryption, anonymization, and pseudonymization
Provide Guidance & Enablement: Prescribe guidance and techniques for data anonymization and pseudonymization to Data Engineering and ML teams
Collaborate Cross-Functionally: Partner with security, legal, IT, engineering, and AI teams for compliance and technical implementation
Support Compliance: Ensure global privacy compliance (GDPR, CCPA, etc.) across modern data stack (Snowflake, Databricks, CDP, Looker, AWS)
Innovate Privacy Solutions: Drive development of privacy-preserving features, tools, and automation for data lifecycle management
Maintain Documentation: Build and update technical documentation covering data flows, tracking technologies, retention policies, and privacy controls
Requirements
5+ years of experience in privacy engineering, data protection, or security engineering
Passion for privacy, trust, and data protection in modern cloud platforms
Strong analytical and problem-solving skills
Excellent communication skills
Background in secure coding practices, code auditing, and privacy-preserving design patterns
Proficiency with Python or other scripting languages for automation and privacy tool development
Hands-on experience with cloud environments and integration into data pipelines
Awareness of data protection regulations and principles (GDPR, CCPA) and ability to translate legal guidance into technical processes
Familiarity with privacy tech platforms (e.g. DataGrail, Transcend), Data Subject Requests, cookie and tracking technology management platforms (CMPs) is a plus
Experience embedding privacy into modern data platforms (CDPs, Snowflake, Databricks, analytics tools, AI/ML workflows) is highly beneficial
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