Senior Data Protection Engineer

Responsibilities

• Translate policy, regulatory, privacy, and risk requirements into practical controls and sustainable operating processes.
• Implement and improve data protection processes, controls, and technologies in an enterprise environment.
• Hands-on knowledge of data discovery, classification, labeling, access, monitoring, retention, and data loss prevention processes.
• Experience with data protection, classification, governance, monitoring, or data loss prevention tools and related operating processes.
• Communicate clearly with technical and non-technical stakeholders and influence practical data protection decisions.
• Balance data protection requirements, business needs, and operational practicality in a regulated environment.

Requirements

• Bachelor’s degree in information security, information technology, computer science, risk management, or a related field; or equivalent education, certifications, and relevant work experience.
• 5 or more years of experience in data protection, information security, data governance, IT Security, risk management, or a related field.
• Experience supporting or building data protection capabilities, programs, or controls.

Key Competencies

• Develops Talent - Owns personal development and career growth.
• Actively seeks information to understand the rationale, implications, and impact for changes.
• Remains agile by quickly modifying daily behavior, leveraging resources, and trying new approaches to effectively embrace change.
• Identifies and recommends changes to leadership to improve performance.
• Strategically breaks down larger goals into smaller achievable goals and communicates how they contribute to the broader goal.
• Effectively and transparently shares information and ideas with others.
• Tailors the delivery of communication in a way that engages the audience and is easy to understand and retain.
• Unites others towards a common goal.
• Takes ownership of the problem while collaborating with others on a resolution with an appropriate level of urgency.
• Evaluates the implications of new information or events and recommends solutions using decisions that are sound based on what is known at the time.
• Takes action that is consistent with available facts, constraints, and probable consequences.
• Passionately serves internal/external clients with excellence.
• Maintains a growth mindset staying current with developments and trends in areas of expertise influencing client satisfaction both internally and externally.
• Understands data, metrics, and/or financial information, and how they tie to client satisfaction and business outcomes related to position, client, and/or team.
• Nurtures client relationships by listening, prioritizing, and acting responsibly to meet client needs, mitigate risk, and add shareholder value.
• Seeks diverse relationships to learn more about people from other cultures and backgrounds.
• Gathers information with curiosity and humility to learn more about people from other cultures and backgrounds including impacts on norms, behaviors, and expectations (e.g., social norms, decision-making approaches, and preferences).
• Advocates for diverse perspectives.
• Continually examines own biases and behaviors to avoid stereotypical responses.

Qualifications and Education

• Bachelor’s degree in information security, information technology, computer science, risk management, or a related field; or equivalent education, certifications, and relevant work experience.
• 5 or more years of experience in data protection, information security, data governance, IT Security, risk management, or a related field.
• Experience supporting or building data protection capabilities, programs, or controls.

Preferred Qualifications

• Experience with Microsoft Purview, Varonis, or comparable data protection, classification, governance, or DLP platforms.
• Experience using AI-enabled data protection capabilities, including data security posture management, sensitive data discovery and classification, access risk analysis, anomalous behavior detection, automated remediation workflows, and secure adoption of generative AI tools through platforms such as Microsoft Purview, Varonis, or comparable technologies.
• Familiarity with data governance, privacy, or security frameworks such as DCAM, NIST Privacy Framework, FFIEC guidance, or similar industry practices.