Privacy Management & Data Protection Topics
Privacy compliance, data protection frameworks, privacy incident investigation, and regulatory requirements. Covers privacy impact assessments, data classification, regulatory interpretation, and privacy-first operational practices.
Data Protection and Governance Strategies
Covers practices to protect and govern data throughout its lifecycle. Topics include protecting data at rest and in transit through encryption and key management; data classification and access control models; backup, recovery, and disaster recovery strategies; retention and secure disposal policies; auditing and logging for compliance; masking and anonymization techniques for privacy; and regulatory considerations when designing data protection measures.
Compliance Risk Assessment and Prioritization
Covers the end to end process for identifying and prioritizing compliance obligations and risks across an organization. Candidates should be able to describe how to define the compliance universe by cataloging applicable regulations, laws, standards, contractual requirements, and internal policies and then map those obligations to business processes and systems. Includes approaches to risk assessment such as identifying threats, vulnerabilities, and impacts, using risk formulas for likelihood and severity, and choosing between quantitative and qualitative techniques. Includes risk scoring, risk based testing and test case prioritization, and methods to balance testing thoroughness with time and resource constraints. Encompasses compliance gap analysis, development of phased implementation roadmaps, sequencing of remediation work, trade off decisions between quick wins and long term initiatives, and communication of priorities and findings to stakeholders. Also covers operationalization practices for tracking progress, measuring risk reduction, and adjusting prioritization as business context or regulatory requirements change.
Data Governance and Privacy Programs
Design and operate data governance and privacy programs that ensure data quality, lawful processing, and sustained compliance. Cover data inventory and mapping, data classification schemes, data quality rules and remediation processes, ownership and stewardship models, data lifecycle management, privacy by design principles, data protection controls, vendor and processor management, individual rights handling, incident response for privacy events, monitoring and audit mechanisms, and reporting to regulators. Explain how data governance, data quality, and privacy program components interconnect to enable trustworthy and auditable data usage while supporting business analytics and product needs.
Google Cloud Platform Data Protection
Assess how the candidate protects data on Google Cloud Platform including encryption at rest and in transit, field level encryption for personally identifiable information, key lifecycle and rotation using Cloud Key Management Service, secrets management for credentials, data classification and access controls, data residency and retention controls to meet regulations, and privacy preserving techniques to support data subject rights. Answers should cover balancing protection with performance and operational needs.
Data Security Privacy and Governance
Data centric considerations covering classification, governance, protection, and quality. Topics include data classification and labeling, encryption strategies and key management for stored and in transit data, data residency and sovereignty requirements, privacy regulations and compliance, data lifecycle and retention policies, access controls and delegation, data governance frameworks, addressing shadow information technology and data mobility, and practical data quality concerns and how they interact with privacy and access controls.