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The incumbent will beinvolved in server and endpoint security strategy and technical governance,product configuration standards definition and security engineering advisory.
As a member of theSecurity Engineering team, the incumbent will be part of the product lifecyclemanagement for the Group Information Security (GIS) technical capabilities.This include product implementation, solution architecture, engineering,production support and service delivery/management, and provide infrastructuresecurity configuration standards definition and technical security assuranceover servers and endpoints managed by the infrastructure and platform team.
Responsibilities:
Develop and maintainthe server and endpoint security roadmaps and plan for future enhancements andcapabilities as party of continuous improvement process
Manage productlifecycle for the Group Information Security (GIS) technical capabilities overserver and endpoint security solutions which include but is not limited toanti-virus, anti-malware, firewalls, intrusion detection/prevention systems,and other relevant technologies
Provide productionsupport and monitoring to ensure control efficacy and solution reliability& stability
Product research anddefine requirements for new projects, perform product evaluation and technicalProof of Concept
Support the developmentof server and endpoint security policies, standards, and procedures to ensurecompliance with regulatory requirements and industry best practices
Provide support for allaudit and regulatory requests
Provide guidance andadvisory for technical security questions that are operational in nature
Review and grantexceptions to security policy settings that have operational implications forvalid business activities (e.g. endpoint policy exception required forapplication functionality)
Education:
Degree in Engineering /Computer Science / IT / Cyber Security from a recognized education institution
Professional securityrelated qualifications (e.g., CISSP, CISA, CISM, ITIL, etc.) will be favorablealthough not mandatory
Technical Skills:
Overall experience 8 to12 years of experience
In-depth knowledge ofsystem protection and security incident response
Hands-on experience inboth on-premises and SaaS Endpoint Protection Platform (EPP) and EndpointDetection & Response (EDR) solutions (e.g., Trend Deep Security, TrendVision One, Symantec SEP, Trellix ENS, CrowdStrike, Cortex XDR, Sentinel One,etc) with the ability to design, size and operationalize solution across largeenterprise environment
Proven experienceleading relevant security programs in large organizations
Strong understanding ofregulatory requirements such as MAS TRM, PCI DSS, etc.
Experience withsecurity monitoring and data analysis using Splunk
Familiarity with ITILprocesses (especially Change, Incident and Service Management)
Familiarity withServiceNow, Jira, or other ITSM platforms
Scripting skills (e.g.,Python, Bash) for operational or automation efficiency will be advantageous
Soft Skills:
Excellentcommunication, leadership, and collaboration skills
Process aware mindset
Strong analytical andproblem-solving skills
Effective timemanagement and organizational skills
Team player, includingability to establish and maintain effective working relationships within andacross the organization
Job ID: 151133447
Skills:
Itil Processes, Servicenow, Jira, Sentinel One, Data analysis using Splunk, Trend Vision One, Trend Deep Security, Symantec SEP, Security Monitoring, Trellix ENS, CrowdStrike Cortex XDR
Skills:
VMware, Servicenow, Windows Server, Citrix, MECM, PowerShell, Scom, Failover Clustering, Pki, Ansible, Nutanix, Vsan, Azure, SCCM, AWS, Entra ID, Active Directory
Skills:
Servicenow, Itil Processes, JIRA, Salesforce, Escalation Management, Stakeholder Management, Service Desk Operations
Skills:
Servicenow, Incident Management, Problem Management, ITIL 4, Root Cause Analysis, ishikawa, 5 Whys, Kepner-Tregoe
Skills:
Data Governance, Data Architecture, Data Security, Applied Machine Learning techniques, AI governance, Data KRIs, Risk management frameworks, AI explainability, Industry best practices, Data quality monitoring, Algorithmic bias, Regulatory Requirements