Privacy Validation Engineer, Privacy Data Protection Office

The Privacy Data Protection Office (PDPO) is responsible for driving privacy and data protection across TikTok’s global product ecosystem. We work across engineering, product, legal, compliance, and data governance teams to identify privacy risks and ensure that user data is handled safely, responsibly, and consistently.

In the field of data protection, we are building a solid infrastructure covering areas such as data retention, data classification, and database storage to address major data protection risks. As our governance capabilities continue to evolve, we are also building platforms and engineering capabilities that can provide objective, data-driven insights into the effectiveness of these protection mechanisms from an audit perspective.

The Privacy Validation Engineering Team is responsible for building automated and intelligent verification capabilities to measure whether data protection policies and controls are effectively implemented across the technology stack. By validating the actual behavior of systems against privacy requirements and policies, we aim to identify systemic risks, strengthen privacy governance, and provide actionable insights to engineering teams. Our current focus includes end-to-end verification of data retention policies, covering the full data lifecycle across products, backend services, databases, and data platforms.

We are looking for a Privacy Validation Engineer to help us build scalable validation platforms and engineering solutions that make privacy protection measurable, observable, and continuously verifiable.

• Build automated and intelligent privacy verification systems to assess whether data protection policies and controls are effectively implemented across TikTok’s technology ecosystem.
• Design and implement end-to-end verification of data protection requirements, with an initial focus on data retention across data collection, transmission, storage, processing, and deletion.
• Build automated and intelligent privacy validation capabilities to verify whether data protection policies and controls are effectively implemented, with an initial focus on end-to-end data retention verification.
• Design, develop, and execute functional testing for privacy-related features across mobile applications (iOS/Android), web frontend, backend services, and data processing pipelines.
• Develop test automation, validation tools, and internal frameworks/platforms, collaborating with automation and performance testing teams to improve testing productivity, coverage, and scalability across multiple technology stacks.
• Collaborate with engineering, legal, compliance, and data governance teams to collect privacy governance facts, identify systemic risks, and provide actionable insights to improve privacy protection and project quality.

Minimum Qualification(s)

• BS/MS degree in a relevant field, such as Computer Engineering, Electrical Engineering, Computer Science, or Cybersecurity.
• Fundamental knowledge of distributed systems and data protection concepts, such as encryption, access control, auditing, and data handling, with a good understanding of frontend-backend-data interaction patterns.
• Testing experience across multiple technology layers, including frontend, backend, and data/infrastructure layers, rather than deep expertise in a single platform.
• Excellent problem-solving and analytical skills, with the ability to investigate issues across multiple systems and identify potential privacy or data protection risks.
• Strong communication and collaboration skills, with the ability to work effectively with global teams, including engineering, legal, compliance, and data governance stakeholders.
• Strong interest in privacy protection and end-to-end quality assurance, with a focus on ensuring user data is handled securely and consistently across the technology stack.

Preferred Qualification(s)

• Familiarity with Redis, NSQ, ZeroMQ, Kafka, Docker, Kubernetes (K8s), Hive, Spark, or similar technologies.
• Experience with data validation, data pipelines, distributed systems, or cross-system data consistency is a plus.
• Experience in privacy engineering, security testing, data governance, or compliance-related technology is a plus.