Company Privacy Landscape Questions

Demonstrate company specific understanding of privacy and data protection considerations. This covers the organization public privacy commitments, data handling scale and types, major privacy initiatives, known privacy risks or incidents, applicable privacy regulations for their markets and products, data governance practices, and how privacy requirements influence product design, analytics, and third party integrations. Interviewers look for evidence you researched the company privacy context and can discuss implications for compliance, user trust, and practical privacy engineering or policy tradeoffs.

EasyTechnical

0 practiced

Explain in plain terms the GDPR and CCPA/CPRA rights most relevant to a BI analyst building dashboards (for example: right of access, right to erasure, right to opt-out of sale/sharing, data portability). For each right, describe a concrete constraint it creates for BI reporting and one practical approach to comply while retaining analytical value.

MediumTechnical

0 practiced

After a privacy incident where an analyst exported a table including raw user emails from a dashboard, stakeholders request urgent ad-hoc metrics. As a BI analyst, explain the immediate steps you would take to deliver results safely: include temporary controls (sanitized extracts, sign-offs), documentation of the exception, and follow-up remediation actions to prevent recurrence.

MediumTechnical

0 practiced

Walk me through a Data Protection Impact Assessment (DPIA) for a new analytics pipeline that will join marketing CRM data with behavioral event streams. Define scope, stakeholders, dataflow mapping, risk assessment methodology, mitigations, and acceptance criteria you would include for sign-off by privacy and legal.

HardTechnical

0 practiced

Develop a quantitative scoring framework to assess privacy risk for third-party vendors involved in BI (data warehouses, ETL platforms, visualization tools). List scoring factors (data sensitivity, scope of access, subprocessors, certifications, contractual protections), suggested weights, and how vendor scores should influence procurement decisions and ongoing monitoring.

MediumTechnical

0 practiced

Provide pseudocode (Python or SQL) for an ETL step that aggregates user-level events into daily metrics without persisting raw identifiers. Show how you would create reproducible hashed IDs using a managed salt, outline salt rotation considerations, and explain the trade-offs related to re-identifiability and joinability.

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