Data Security Engineer

Data Security Engineer - Remote

Job Overview:
This organization is a leading nonprofit that simplifies healthcare administration through trusted data and technology solutions, helping providers, payers, and patients exchange information efficiently and securely. As a Data Security Engineer, you will play a critical role in protecting sensitive data across the enterprise supporting regulatory compliance, operational resilience, and the mission to serve as a trusted utility for the healthcare industry.

Responsibilities:

Data Protection & Security Strategy:

• Design, implement, and mature enterprise-wide data protection strategies across structured and unstructured data environments on-premises, cloud, and endpoints.

• Safeguard sensitive information, including PII, PHI, and other critical business data.

• Lead the definition and implementation of data protection policies, frameworks, and security guardrails aligned with industry standards and regulatory requirements.

Data Inventory & Classification:

• Partner with data owners and teams to identify and inventory critical data assets.

• Implement automated and programmatic classification of sensitive data using tools like Microsoft Purview and other CASB solutions.

• Conduct data security architecture reviews, identify control gaps, and drive remediation.

Foundational Big Data & Analytics Security:

• Bring hands-on experience with Big Data ecosystems, including data lakes, data pipelines, and large-scale ETL environments.

• Implement and enforce role-based access controls (RBAC) for Big Data platforms.

• Ensure security controls for data masking, tokenization, and anonymization are embedded in data workflows.

• Collaborate with engineering and analytics teams to build secure data pipelines across both relational and NoSQL systems.

Security Solutions Architecture:

• Architect and implement security patterns, requirements, and architectures across data domains.

• Oversee secure implementation of encryption (in transit, at rest, and in use), tokenization, masking, and anonymization in collaboration with Data Science and Technology teams.

• Embed security into modern architectures, including APIs, microservices, ETL pipelines, and streaming platforms.

AI & MLOps Security:

• Provide architectural oversight for AI agents and LLM pipelines, ensuring adoption of Agentic security principles.

• Guide secure design for AI/GenAI systems, including model governance, adversarial testing, and emerging risk mitigation (e.g., prompt injection, data leakage, data poisoning).

• Apply MLOps security controls across model training, validation, deployment, and drift monitoring.

Policy Development & Enforcement:

• Develop and maintain data protection policies aligned with regulatory standards (e.g., HIPAA).

• Apply and tune DLP policies across email, cloud, USB, printing, and endpoint channels.

• Analyze DLP alerts and logs to identify anomalies, reduce false positives, and escalate incidents.

Monitoring & Threat Detection:

• Build dashboards, alerts, and metrics for real-time monitoring of data protection events.

• Implement and manage data rights enforcement mechanisms to ensure appropriate access and usage of sensitive data.

• Support integration of rights management with automated classification and labeling systems.

Data Security Posture Management (DSPM):

• Contribute to deployment and tuning of DSPM tools such as Wiz to enhance visibility and control.

• Support initiatives to shift from reactive to proactive, risk-based protections.

Backup, Recovery & Process Automation:

• Collaborate with infrastructure teams to align backup and recovery strategies with data protection objectives.

• Integrate DLP and DSPM tools with SIEM for incident response, ticketing, and compliance reporting.

• Support orchestration of triage, review, and remediation workflows to reduce manual overhead.

Cross-Functional Collaboration:

• Work closely with teams across the organization to align protection strategies with business operations.

• Provide training and documentation to business units on data protection best practices.