Security Engineer

Role: Security Engineer - Data Loss Prevention

Location: Mountain View CA (100% Onsite)

C2C

DETAILED JOB DUTIES

Skill Set Security Engineer - Data Loss Prevention (DLP) Role

Must-Have Skills (Non-Negotiable) DLP

1. Proactive & Real-Time Monitoring of DLP Incidents
1. Continuous monitoring of security events to detect and respond to data loss threats.
2. Examples: Implementing real-time alerts and proactive DLP incident tracking.
3. Tools: Netskope, Zscaler, CrowdStrike, CyberArk (DLP and Privileged Access Management tools).
2. Identification & Investigation of DLP Incidents
1. Deep dive analysis into security alerts, insider threats, and potential breaches.
2. Examples: Using AI/ML to identify threat patterns and analyze root causes of incidents.
3. Tools: AWS Security Hub, Python, JSON, Jira (for workflow tracking and investigation).
3. Preventive & Corrective Actions
1. Developing and implementing preventive security measures to reduce risks.
2. Examples: Policy enforcement for sensitive data access controls and anomaly detection.
3. Tools: CyberArk (Privilege Elevation Security), AWS IAM, Security Policies.
4. Containing & Mitigating DLP Incidents
1. Rapid response and containment strategies for active security threats.
2. Examples: Automating incident containment through AI-driven security response.
3. Tools: CrowdStrike (Threat Intelligence), AWS Lambda (Automated Remediation).
5. Redesigning & Enhancing DLP Policies
1. Continuous improvement and adaptation of DLP security policies to evolving threats.
2. Examples: Regular security audits and policy fine-tuning to minimize insider risk.
3. Tools: DLP rule configuration in Netskope, Zscaler, and AWS Security Policies.
6. Automation in Detecting DLP Incidents
1. Developing and deploying automated DLP detection mechanisms.
2. Tools: AWS (Lambda, Security Hub, GuardDuty), Python, JSON for automation scripting.

Good-to-Have Skills (Preferred but Not Mandatory) - DLP

1. AI/ML Security Expertise
1. Securing AI-driven security systems and automation.
2. Examples: Leveraging AI for predictive analytics in security threat detection.
2. Cloud Security & DevSecOps Experience
1. Implementing security controls within DevOps pipelines.
2. Examples: Secure SDLC integration using AWS security tools.
3. Endpoint & Privileged Access Security
1. Strengthening endpoint protection and access controls.
2. Tools: CyberArk (Privilege Management), CrowdStrike (Endpoint Security).