Senior Manager, Privacy Engineering

Responsibilities

• Lead the Privacy Engineering team’s strategy, roadmap, and execution across privacy infrastructure, data governance, and privacy-by-design initiatives
• Hire, coach, and develop a team of privacy engineers while establishing clear operating rhythms, priorities, and technical standards
• Guide the design and delivery of scalable privacy controls, including data discovery, classification, access controls, audit logging, retention, deletion, lineage, encryption, and key management
• Partner with Legal, Compliance, Security, Product, Data, Machine Learning, and Infrastructure teams to translate privacy requirements into practical technical solutions
• Oversee privacy reviews, technical risk assessments, and threat modeling for new products, data flows, models, and platform capabilities
• Define metrics and communicate progress, tradeoffs, dependencies, and risks to technical and cross-functional stakeholders

Minimum Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience
• 8+ years of experience in engineering, including at least 3 years of direct people management experience
• Experience leading engineering teams responsible for production software, platform, privacy, security, or data systems
• Experience designing, building, or operating privacy, security, data governance, or data platform capabilities in production environments
• Experience translating privacy, security, compliance, or regulatory requirements into technical controls
• Experience working with cross-functional partners such as Legal, Compliance, Security, Product, Data, or Machine Learning teams

Preferred Qualifications

• Knowledge of privacy-by-design principles, data minimization, purpose limitation, consent, retention, deletion, and data subject rights
• Knowledge of privacy and data protection regulations or frameworks such as GDPR, CCPA/CPRA, GLBA, FCRA, or similar requirements
• Experience with privacy reviews, threat modeling, risk assessments, data inventories, lineage systems, or automated policy enforcement
• Experience building privacy or governance controls for machine learning, AI, financial services, lending, or other regulated data environments
• Ability to communicate technical privacy tradeoffs clearly across engineering, legal, product, security, and business audiences