Data Protection Lead Engineer

Ford's Cyber Security Data Protection team is the frontline defense for our global digital transformation, safeguarding the company's most critical data assets.

As a Data Protection Lead Engineer, you will be a subject matter expert in Microsoft Purview and Sentinel, applying machine learning and AI techniques to strengthen data classification, threat detection, and policy enforcement across a global enterprise.

Responsibilities

• Own the technical strategy and architecture for Ford's global DLP program within Microsoft Purview and Sentinel, setting direction for policy design, tooling, and roadmap.
• Apply machine learning and AI techniques to improve data classification accuracy, reduce false positives, and strengthen threat detection at enterprise scale.
• Lead the design and implementation of advanced DLP policies, balancing security effectiveness against business usability across global regions and business units.
• Architect and oversee automated workflows and data pipelines that transform raw DLP telemetry into actionable risk insights.
• Design, manage, and govern RESTful APIs that integrate DLP tooling with the broader cybersecurity ecosystem.
• Serve as the escalation point for complex DLP incidents, leading investigation, remediation, and root-cause analysis for high-risk data loss events.
• Define and deliver executive-level DLP metrics and reporting, giving senior leadership visibility into global data loss risk posture and program maturity.
• Partner with senior stakeholders across business and technology teams to translate ambiguous requirements into technical roadmaps, negotiating scope, feasibility, and resourcing.
• Formalize and present architecture decisions and technical strategy to leadership and cross-functional review boards, securing buy-in and approvals.
• Drive continuous improvement of DLP tooling, processes, and detection capabilities, championing adoption of emerging ML/AI security technologies.
• Lead technical retrospectives and process improvement initiatives, identifying systemic gaps and driving org-wide fixes rather than one-off patches.
• Mentor and develop junior and mid-level engineers, providing technical guidance, code/architecture review, and career development support.

Qualifications

• Engineering or equivalent degree in Computer Science, Cybersecurity, or related field.
• 5+ years in Cybersecurity, with 3+ years focused specifically on DLP or data governance.
• 3+ years hands-on experience with Microsoft Purview and/or Sentinel in a large enterprise environment.
• 2+ years hands-on experience with Microsoft Azure or Google Cloud Platform, including securing data across cloud environments.
• Demonstrated experience applying ML/AI concepts to a security or data protection use case.