Job description
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 DLP Senior Security Engineer, you'll 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.
- 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 (GCP), including securing data across cloud environments.
- Demonstrated experience applying ML/AI concepts to a security or data protection use case.
- Own the technical strategy and architecture for Ford's global DLP program within Microsoft Purview and Sentinel (or equivalent platform), 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 (Python, Logic Apps) 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.
- Act as a technical role model and change agent, representing the DLP team in broader security architecture discussions and influencing enterprise-wide data protection strategy.
Proactively identify and remove cross-team roadblocks, collaborating with adjacent security, privacy, and infrastructure teams to keep initiatives on track.