01Overview
Cybersecurity and Data privacy Engineer - RegTech Minimum 7 years of experience in cybersecurity, application security, cloud security, data privacy, security engineering or risk/control roles. Strong understanding of IAM, RBAC, encryption, secrets management, API security, secure SDLC, vulnerability management and cloud security controls. Experience with Azure or other cloud security services, including identity, Key Vault, logging, monitoring, private networking and security posture management. Understanding of privacy principles including PII handling, minimization, retention, masking, access control and data transfer controls. Experience conducting or supporting security reviews, threat modeling, penetration test remediation, vulnerability triage and control validation. Ability to work with engineering teams to convert security requirements into practical implementation guidance. Strong documentation skills for security controls, risks, remediation plans and audit/client-review evidence. Define and review security requirements across authentication, authorization, RBAC, tenant isolation, encryption, secrets management, API security and secure deployment. Design and validate data privacy controls for sensitive data, PII handling, retention, masking, deletion, access logging and secure data movement. Support threat modeling, secure architecture review, security test planning, vulnerability management and remediation tracking. Work with DevOps teams to implement security controls around cloud configuration, Key Vault, managed identities, private networking, security monitoring and policy guardrails. Review application security patterns including input validation, access control, session handling, secure logging, audit events and data leakage prevention. Support readiness for external certifications and client security reviews such as SOC 2, ISO 27001, ISO 27701, ISO 42001, SOC 1 and CSA STAR where applicable. Contribute to security documentation, control mappings, privacy impact inputs, security questionnaires and audit evidence. Partner with AI engineers to design AI usage controls, prompt/data privacy rules, AI output logging and responsible AI guardrails. .
