Senior Data Security Engineer

Senior Data Security Engineer.

Location: #Remote.
Salary: Competitive.
Employer: Awin.

Responsibilities:
• Architect and implement Awin's data security framework in partnership with the Security Architect. Build and operationalise the classification taxonomy, sensitivity tiers, and data handling standards that will underpin all downstream DLP, DSPM, and AI governance controls.
• Support the implementation of Awin's data classification programme —labelling policies, and classification coverage across all data environment where sensitive data is processed or stored.
• Own the implementation of DLP policies that prevent sensitive data from being shared, exported, or transmitted in breach of Awin's confidentiality risk appetite. Define policy architecture, alert thresholds, and enforcement logic. Work with Internal IT on deployment and tuning, and maintain audit-ready records of DLP events and enforcement actions.
• Operationalise data security posture management tooling to provide visibility and control over how sensitive data flows to AI tools and third-party services. Ensure that AI data governance controls are technically enforceable, supporting Awin's AI risk appetite statements and the requirements of the AI governance framework.
• Act as the data security domain expert for the Security Architecture function. Work closely with the Security Architect to provide specialist input into architecture reviews, product designs, and technology assessments where data security considerations are material.
• Engage directly with stakeholders to understand how sensitive data flows across the organisation, and to ensure that data security requirements integrate coherently with the broader data governance framework.

Requirements:
• Demonstrable experience in a dedicated, senior data security role.
• Proven track record of implementing data classification frameworks in complex, multi-cloud or hybrid environments.
• Hands-on experience leading DLP programme and implementation and ongoing management.
• Experience engaging with data engineering, data architecture, or data governance teams — able to work credibly alongside experienced data professionals on shared problems.
• Exposure to AI governance, DSPM, or shadow AI detection is desirable — the right candidate will develop and lead this capability in the role.
• Exposure to security architecture processes — architecture reviews. reference architecture development and architectural decision making process — is desirable.
• Data classification framework design — sensitivity label schema, sensitive information type definition, auto-labelling policy configuration.
• DLP policy architecture, implementation, and tuning across endpoint, network, and cloud channels.
• Cloud data environments — AWS S3 and data services, Azure data services, M365 data flows; understanding of where sensitive data typically resides and how it moves across these platforms.
• CASB concepts and tooling (Defender for Cloud Apps or equivalent) and how CASB and DLP capabilities interact and complement each other.
• GDPR and data protection obligations knowledge and how regulatory requirements translate into technical controls.
• AI service data handling models — understanding how tools including Microsoft Copilot, ChatGPT, and third-party AI services handle, retain, and potentially train on submitted data, and how to assess and mitigate that risk.
• Broad awareness of data governance frameworks — including data cataloguing, lineage, access governance, and data quality — sufficient to engage meaningfully with data governance stakeholders and position data security as an enabler rather than a constraint.
• Able to operate with a high degree of autonomy — this role is building a capability from a fragmented baseline.
• Strong credibility with senior technical stakeholders — able to engage as a peer with the Security Architect and experienced data professionals.

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