Senior Data Security Engineer

HF Sinclair is seeking a Senior Data Security Engineer in Dallas, Texas. Serves as the technical authority responsible for defining and operationalizing the enterprise data security execution model. This role is accountable for translating data security intent (governance, privacy, policy) into repeatable, enforceable, and observable controls across production environments, with particular focus on application, API, analytics & automation, and AI-driven data access paths.

As the first dedicated data security engineering role, this position provides hands-on technical leadership while simultaneously shaping architecture standards, maturity targets, and implementation sequencing. The role partners closely with Cybersecurity Architecture, Cloud Engineering, Data & Analytics, and Application teams to ensure data security capabilities are designed for execution speed, not theoretical completeness.

This role intentionally prioritizes reducing current exposure before enabling advanced use cases. Secure analytics and AI are treated as outcomes of maturity, not parallel initiatives.

HF Sinclair is seeking a Senior Data Security Engineer in Dallas, Texas. Serves as the technical authority responsible for defining and operationalizing the enterprise data security execution model. This role is accountable for translating data security intent (governance, privacy, policy) into repeatable, enforceable, and observable controls across production environments, with particular focus on application, API, analytics & automation, and AI-driven data access paths.

As the first dedicated data security engineering role, this position provides hands-on technical leadership while simultaneously shaping architecture standards, maturity targets, and implementation sequencing. The role partners closely with Cybersecurity Architecture, Cloud Engineering, Data & Analytics, and Application teams to ensure data security capabilities are designed for execution speed, not theoretical completeness.

This role intentionally prioritizes reducing current exposure before enabling advanced use cases. Secure analytics and AI are treated as outcomes of maturity, not parallel initiatives.

• Define and maintain data security reference architectures and control patterns focused on:
  • Application-mediated data access
  • API exposure and service-to-service data flows
  • Automation, orchestration, and machine-driven access, AI/ML workloads, etc.
• Define and monitor data security capability maturity across structured, unstructured, and application-centric domains, aligned to the enterprise cybersecurity taxonomy.
• Translate architectural intent into implementable standards and technical design criteria that engineering teams can execute without ambiguity.
• Define & maintain enterprise data classification, labeling & protection standards across structured & unstructured data.
• Participate in architecture reviews & modernization initiatives to ensure secure data handling requirements are incorporated into application, cloud, analytics, integrations, & automation solutions

• Lead technical efforts to identify and reduce existing data exposure, with emphasis on:
  • Access path patterns and permissions across SaaS, cloud service, third-party integrations, and business applications
  • Application and API data flow monitoring
  • Data protection capabilities supporting classification, monitoring, access governance, & data loss prevention requirements
• Design and implement controls that operate at execution points, including:
  • Data access monitoring tied to application context
  • Enforcement patterns beyond static DLP or perimeter controls

• Serve as the technical advisor for securing data used in analytics, automation, and AI initiatives.
• Collaborate with peer IT and business teams to embed security controls into data pipelines, feature stores, and model interaction layers.
• Explicitly sequence AI-related security work to avoid increasing risk through premature enablement.

• Provide targeted cloud security…