Cyber Security Engineer - Data Security

HealthFirst•Herminie, PA

1d•$99,100 - $156,485•Onsite

About The Position

We are seeking a Cyber Security Engineer – Data Security to design, implement, and continuously improve security capabilities that protect sensitive data across the enterprise. This is a hands-on security engineering role focused on understanding where sensitive data resides, how it moves, who and what can access it, and ensuring appropriate controls are implemented throughout the data lifecycle. The engineer will work closely with Security, Infrastructure, Cloud, Data, Application, and AI teams to implement scalable data protection capabilities across cloud, SaaS, application, database, endpoint, and emerging AI environments.

Requirements

Technical Degree in Computer Science, Cyber Security and/or a High School Diploma/GED from an accredited institution along with equivalent work experience
Entry-level experience in at least two of the following areas: security engineering, network penetration, incident response, threat hunting, and governance risk & compliance

Nice To Haves

3+ years of experience in cybersecurity, security engineering, cloud security, data security, or a related technical discipline.
Hands-on experience implementing or operating enterprise data protection, DLP, DSPM, or data security technologies.
Strong understanding of data security principles including discovery, classification, access control, encryption, data loss prevention, and monitoring.
Experience securing data across cloud, SaaS, database, and application environments.
Understanding of IAM concepts including authentication, authorization, RBAC, least privilege, and privileged access.
Experience with at least one major cloud platform such as Azure, AWS, or Google Cloud.
Experience with security automation, scripting, or APIs; Python, PowerShell, or comparable experience preferred.
Strong understanding of security architecture and common data-exfiltration techniques.
Ability to troubleshoot complex technical issues and translate identified risks into practical engineering solutions.
Strong written and verbal communication skills with the ability to collaborate across security and engineering teams.
Experience implementing or operating DSPM/CNAPP/data security platforms in large enterprise environments.
Experience with enterprise DLP technologies across endpoint, email, cloud, and SaaS environments.
Experience with Microsoft Purview, Microsoft Defender, or comparable enterprise data security technologies.
Experience securing structured and unstructured data across databases, data lakes, warehouses, object storage, and collaboration platforms.
Experience with encryption, key management, tokenization, masking, or secrets-management technologies.
Experience developing automated data security controls and remediation workflows.
Experience with Infrastructure as Code and incorporating security controls into cloud deployments.
Understanding of data security considerations for generative AI and agentic AI, including preventing inappropriate access to or disclosure of sensitive information.
Familiarity with data governance, retention, privacy, and regulatory requirements.
Experience protecting PHI, PII, financial, or other sensitive data in a regulated environment.

Responsibilities

Design, implement, and maintain enterprise data security controls across cloud, SaaS, applications, databases, endpoints, and AI platforms.
Implement and improve data discovery, classification, labeling, and protection capabilities for sensitive and regulated data.
Engineer and operate Data Security Posture Management (DSPM) capabilities to identify sensitive data, excessive exposure, misconfigurations, and inappropriate access.
Develop and tune Data Loss Prevention (DLP) controls across endpoint, cloud, email, collaboration, and SaaS environments.
Assess how sensitive data is stored, processed, transmitted, and accessed and recommend appropriate security controls.
Identify excessive or inappropriate access to sensitive data and partner with IAM, Privacy and platform teams to implement least-privilege access.
Support encryption, tokenization, masking, secrets protection, and key-management strategies where appropriate.
Develop monitoring and detection capabilities for suspicious or unauthorized access, movement, and exfiltration of sensitive data.
Automate data security controls, assessments, monitoring, and remediation using APIs, scripting, and security tooling.
Perform security assessments and threat modeling for systems that store or process sensitive information.
Partner with application, cloud, data, and AI engineering teams to incorporate data protection requirements into system designs.
Support incident investigations involving potential data exposure or exfiltration.
Develop technical standards, security patterns, and engineering guidance for protecting sensitive data.