Data Security Specialist

Data Security Engineer – Cloud, DLP & Automation Location: London, United Kingdom Industry: Technology / Online Delivery & Digital Platforms Employment Type: Full-time Work Arrangement: London-based About the Role A leading global digital platform is seeking a Data Security Engineer to strengthen the protection of sensitive structured and unstructured data across cloud-native and enterprise environments. This role sits at the intersection of data security engineering, automation, cloud security and privacy . You will translate data security architecture and governance requirements into scalable technical controls, while building automated guardrails that reduce risk without slowing down engineering teams. The role has a strong focus on DLP, encryption, data discovery, Policy-as-Code, CI/CD security, Infrastructure-as-Code and AI-related data security . Key Responsibilities

• Deploy and manage enterprise Data Loss Prevention (DLP) and encryption solutions across network, cloud, endpoint and AI environments.
• Protect sensitive data at rest, in transit and in use.
• Manage automated data discovery and classification pipelines , including controls for AI environments such as training datasets, model inputs and inference logs.
• Partner with Security Architecture teams to embed data protection, cryptography and Infrastructure-as-Code (IaC) security baselines into CI/CD workflows.
• Translate data security and compliance policies into executable Policy-as-Code , including technologies such as OPA.
• Build automated security guardrails and remediation scripts across cloud environments.
• Develop API integrations between security scanning and ticketing platforms.
• Use intelligent automation and AI-driven capabilities to triage, prioritise and tune security alerts while reducing false positives.
• Provide engineering teams with automated feedback, technical documentation and developer-friendly security tools.
• Help prevent data exposure and security issues earlier in the software development lifecycle.
• Collaborate closely with DevOps, Software Engineering, IT, Security Architecture and Privacy teams. Requirements
• Proven experience implementing and managing data security controls within cloud-native or enterprise environments.
• Experience with Data Security Posture Management (DSPM) platforms such as Wiz, Enterprise DLP, cryptography and data classification.
• Strong automation and scripting skills using Python and Bash/Shell .
• Experience translating security requirements and governance policies into automated remediation workflows and CI/CD security gates.
• Strong understanding of cloud security, Infrastructure-as-Code and security automation .
• Practical understanding of AI/ML data security risks , including OWASP Top 10 for LLMs, prompt injection and training-data exposure.
• Experience using AI or intelligent automation to support security activities such as alert triage and data classification.
• Strong understanding of data flows and the ability to turn complex security findings into clear technical guidance.
• Knowledge of data privacy regulations, particularly GDPR .
• Strong collaboration skills, with the ability to work effectively across engineering, infrastructure, security and privacy functions.
• A proactive, solutions-oriented approach to security, with a focus on enabling engineering teams rather than creating unnecessary friction. Key Technologies & Areas Data Security | DLP | DSPM | Encryption | Cryptography | Data Classification | Cloud Security | Python | Bash | CI/CD | Infrastructure-as-Code | Policy-as-Code | OPA | API Automation | AI/ML Security | LLM Security | GDPR What the Role Offers
• Opportunity to work on data security at significant scale across cloud and enterprise environments.
• Exposure to modern AI security, automation and cloud-native security engineering .
• Cross-functional collaboration with engineering, IT, security architecture and privacy teams.
• An international, fast-paced technology environment.
• Focus on building practical security controls that enable innovation while reducing risk.