Data Platforms and AI Access Control Lead

Job Summary

The Data Platform AI Access Control Lead is responsible for ensuring the secure, compliant, and responsible usage of organizational data and AI systems. They bridge the gap between AI engineering, information security, and governance by defining permissions for both human users, Functional Accounts, Service Principles and autonomous AI agents across modern Data Platforms, Analytics ecosystems, AI/ML solutions, and Generative AI environments.

This role will be responsible for establishing secure and compliant Data AI Access ecosystems by integrating IAM, governance, privacy, risk management, and regulatory compliance into Data Platforms and AI Operations.

The ideal candidate will possess deep expertise in Access Management practices in cloud-native data, AI platforms, AI/GenAI security, Role Based Access Control methodologies, regulatory compliance frameworks, and secure engineering practices.

The role requires strong collaboration across Data AI Platform Engineering, IT, Security, Legal, and AI Engineering teams (data science/DevOps/Machine Learning Engineering) to ensure secure, compliant and resilient access control management across Data AI environments.

Key Responsibilities

Data AI Platforms Identity Access Management Governance

Entity Permissions: Define and manage access rights for both human employees and non-human entities (e.g., AI agents, MLOps pipelines, service accounts).

Access Control Matrix: Develop and maintain Role-Based Access Control (RBAC) and Attribute-Based Access Control (ABAC) matrices to dictate who (or what) can read, write, modify, or execute datasets and models.

Principle of Least Privilege: Enforce minimum-necessary access to limit the blast radius ofdata exposure and internal threats

Access Architecture: Design end-to-end authorization frameworks enforcing least-privilege and Attribute-Based Access Control (ABAC) across Azure data estates

IDAM Tools Integration: Manage integrations between IDAM Tools like Microsoft Entra ID (Azure AD), SailPoint, Octa etc and data platforms (Azure Data Lakes, Azure Synapse, Fabric, and Databricks, and AI/ML Platforms).

Lifecycle Management: Automate access provisioning, role mapping, and de-provisioning workflows for clinical, research, and business users.

Define, monitor track Access Controls, risk metrics KPIs against Data Access Management Policies.

Identify and mitigate Data AI-Specific access risks including Data Leakage, Unauthorized Data Exposure, etc.

Maintain enterprise Access Management policies, standards, and control frameworks

Ensure Secure access to enterprise data ecosystems including but not limited to: Data Lakes, Data Warehouses, ETL/ELT Pipelines, Analytics Platforms, Data APIs, Gen AI Applications and Services.

Ensure implementation of secure data access, encryption, masking, retention, and governance controls across Data Engineering MLOps pipelines.

Conduct Data Access (IDAM) Compliance Data Security Assessment: Microsoft Fabric, Azure Data Services, Databricks, Snowflake, enterprise Data AI platforms and Applications by conducting Monthly, Quarterly Half-Yearly and Yearly Access assessment Audits

Maintain SOPs, Runbooks and Knowledge Repositories.

Maintain risk registers and access governance reporting mechanisms.

Support investigations and Perform root cause analysis related to Data AI platform access violation incidents.

Collaborate with Business users, Application Owners, IAM teams to ensure enterprise IDAM policies implemented across Data AI platforms.

Closely working with AI Governance Responsible AI central teams to align with enterprise policies and regulatory expectations.

Implement automated compliance reporting and logging to audit how Data AI models interact with sensitive corporate and customer data.

Lead Compliance Initiatives aligned with ISO 27001, SOC2, GDPR, PCI-DSS, HIPPA, DPDP and AI Governance Frameworks.

Coordinate audits, assessments, and evidence management activities.

Partner with Legal, Privacy, Risk, and Audit teams to ensure regulatory adherence.

Contribute directly to hands-on capacity to Gen AI Operations troubleshooting, and optimisation.

Leadership Stakeholder Engagement

Cross-Functional Liaison: Serve as the primary connector bridging Data Science/AI Engineering teams with Legal, Privacy, and Cybersecurity departments.

Strong collaboration with Data AI Operations Lead, Data AI Security Compliance lead to ensure alignment among all services towers

Mentor Data Engineering, Access and Operations professionals.

Lead awareness and training programs related to Data AI Access Management best practices.

Escalate and remove blockers in a complex, matrix organisation, engaging senior stakeholders as required.

Act as the primary point of contact for Data AI Platform Access Management Programs.

Drive user adoption, service awareness, training coordination, and feedback management.

Ensure Timely Communication to stakeholders during Access Control Shortfalls, High Impact Incidents and Changes.

Support AI Governance and Responsible AI processes through engagement with Architecture Review Boards and AI/ML Architects

Ensuring close alignment to internal external regulatory and compliance requirements, Access Governance Data Lifecycle Audits with no critical or high findings or violation against them.

Key Skills

Identity Access Management

AI GenAI Data Security

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.