Track Lead - Data security and compliance,Presales

Job Summary

a structured Proof of Concept (POC) engagement to evaluate three leading data security and governance platforms — Microsoft Purview, Varonis, and BigID — across five core governance pillars: 1. Data Classification & Labeling – Discover, classify, and label sensitive data across the enterprise. 2. Access Transparency & Governance – Understand who has access to what data, identify excessive permissions, and establish data ownership. 3. Policy-Driven Remediation – Automate enforcement, remediation workflows, and DLP controls. 4. AI Data Risk Governance – Govern data exposure through AI tools including Copilot, ChatGPT, and enterprise AI apps. 5. Continuous Governance & Reporting – Dashboards, compliance reporting, audit trails, and ongoing posture management. The POC will be executed over a 12-week period and will produce a report on recommendations with comparative scoring and architecture guidance to support an informed platform selection decision along with additional 2 weeks for decommissioning of POC environment. 2. POC Objectives 1. Validate each platform's ability to discover, classify, and label sensitive data across Microsoft 365, on-premises file shares, Azure cloud, and SaaS applications. 2. Assess access governance capabilities including permission analytics, data ownership identification, excessive access detection, and entitlement visibility. 3. Evaluate policy-driven remediation workflows including automated enforcement, DLP integration, quarantining, and permission cleanup. 4. Test AI data risk governance features include DSPM for AI, Copilot data governance, AI policy enforcement, and AI interaction monitoring. 5. Measure reporting, dashboarding, and continuous governance capabilities including compliance posture, audit trails, and executive-level visibility.

Key Responsibilities

a structured Proof of Concept (POC) engagement to evaluate three leading data security and governance platforms — Microsoft Purview, Varonis, and BigID — across five core governance pillars: 1. Data Classification & Labeling – Discover, classify, and label sensitive data across the enterprise. 2. Access Transparency & Governance – Understand who has access to what data, identify excessive permissions, and establish data ownership. 3. Policy-Driven Remediation – Automate enforcement, remediation workflows, and DLP controls. 4. AI Data Risk Governance – Govern data exposure through AI tools including Copilot, ChatGPT, and enterprise AI apps. 5. Continuous Governance & Reporting – Dashboards, compliance reporting, audit trails, and ongoing posture management. The POC will be executed over a 12-week period and will produce a report on recommendations with comparative scoring and architecture guidance to support an informed platform selection decision along with additional 2 weeks for decommissioning of POC environment. 2. POC Objectives 1. Validate each platform's ability to discover, classify, and label sensitive data across Microsoft 365, on-premises file shares, Azure cloud, and SaaS applications. 2. Assess access governance capabilities including permission analytics, data ownership identification, excessive access detection, and entitlement visibility. 3. Evaluate policy-driven remediation workflows including automated enforcement, DLP integration, quarantining, and permission cleanup. 4. Test AI data risk governance features include DSPM for AI, Copilot data governance, AI policy enforcement, and AI interaction monitoring. 5. Measure reporting, dashboarding, and continuous governance capabilities including compliance posture, audit trails, and executive-level visibility.

Skill Requirements

Experience in implementation consultation of data security products like MS Purvew, Varonis and Big Id

Other Requirements

excellent communication and project management skillls