Base: $143,000 – $205,000; bonus/equity: not speci...
Enterprise-wide data discovery mechanisms
Data classification and sensitivity standards
Ai and data consumption risk assessment
Design and implement enterprise-wide mechanisms to discover where data resides across on-premises, cloud, SaaS, data lakes, and third-party environments
Job Summary
Design and implement enterprise-wide mechanisms to discover where data resides across on-premises, cloud, SaaS, data lakes, and third-party environments.
Evaluate risks associated with training data, inference data, prompts, and outputs and define controls to prevent unauthorized use of sensitive or IP data in AI workflows.
Serve as a trusted advisor to engineering, data, legal, privacy, and AI teams and lead architectural reviews and influence platform design decisions.
Matching Summary
Design and implement enterprise-wide mechanisms to discover where data resides across on-premises, cloud, SaaS, data lakes, and third-party environments.
Salary
Base: $143,000 – $205,000; Bonus/Equity: Not specified; Benefits: Eligible for additional S&P Global benefits
Skills & Requirements
Must-have
enterprise-wide data discovery mechanisms
data classification and sensitivity standards
AI and data consumption risk assessment
intellectual property protection mechanisms
data protection architecture aligned with zero trust
Nice-to-have
trusted advisor to engineering teams
influence platform design decisions
mentorship of junior architects
Key Requirements
13–15 years of experience
Deep expertise in data discovery, classification, and access governance
Strong understanding of cloud data platforms (AWS, Azure, GCP)
Hands-on experience with DSPM, DLP, encryption, or data governance tools
Solid understanding of AI/ML data pipelines and AI risk management
Experience implementing IP protection techniques
Strong knowledge of regulatory frameworks (GDPR, SOX, privacy, IP protection)