InDepth Engineering Solutions
Cyber Security Engineer
InDepth Engineering Solutions, Palo Alto, California, United States, 94306
Job Description
The Data Protection Engineer will enhance cybersecurity posture by focusing on tactical data protection operations, automation, and tool development to safeguard sensitive information. This role will prioritize securing email systems, endpoints, and other critical platforms while driving proactive data protection strategies aligned with cybersecurity objectives.
The ideal candidate will have a strong technical background, a passion for automation, and the ability to design and implement innovative solutions to protect sensitive data and applications in dynamic environments.
Responsibilities:
Implement and maintain data protection tools ensuring optimal configuration and performance.
Develop and manage policies for data loss prevention (DLP) and detection, including scanning and identifying sensitive data across systems.
Monitor and respond to incidents related to data protection, providing "break glass" support to maintain security and availability.
Integrate and optimize data protection tools with other security platforms using APIs, custom scripting, and orchestration frameworks.
Conduct regular assessments of data protection controls to ensure alignment with evolving threats and organizational goals.
Conduct data discovery and classification initiatives, ensuring sensitive information is adequately protected.
Support implementation of context-aware access controls and ensure ongoing compliance with data security policies.
Work with cross functional stakeholders to understand the sensitivity of their data and how they can support the business to fulfill their Data Protection needs.
Collaborate with IT, Privacy, Legal, and Cybersecurity teams to align tactical data protection measures with broader security objectives.
Qualifications:
Experience implementing and managing DLP tools and configuring data protection policies in corporate environments.
Strong scripting and programming skills (e.g., Python, Bash) to automate data protection operations and enhance tool integrations.
Proven ability to integrate security tools using RESTful APIs and customize workflows for scalable, tactical data protection.
Familiarity with endpoint and email security principles, including hands-on experience with protection and monitoring platforms.
Proficiency with infrastructure-as-code tools (e.g., Terraform, Ansible) to automate and standardize security configurations.
Strong understanding of CI/CD pipelines and version control systems (e.g., Git) for deploying and maintaining secure solutions.
Requirements Extensive programming experience in object-oriented languages (e.g., Python, Go, Java) and SQL, with a proven track record in designing maintainable, scalable, and efficient solutions. Robust expertise in the following areas: distributed data processing, data engineering for high-volume data services, or developing scalable data streaming platforms for real-time analytics. Advanced proficiency in cloud and data infrastructure technologies (e.g., AWS, Databricks, Terraform, Apache Spark, Docker) with deep knowledge of development best practices, CI/CD pipelines, and cloud-native deployment. Comprehensive knowledge of RESTful APIs and data integration techniques to enable efficient, secure, and scalable data flow and communication between security systems and user-facing platforms. Strong familiarity with infrastructure-as-code tools such as Terraform or Ansible to automate and standardize security configurations across diverse environments. Hands-on experience with CI/CD pipelines, version control systems (e.g., Git), and modern software development practices to ensure high standards of consistency, quality, and automation in deploying and updating security tools.
The ideal candidate will have a strong technical background, a passion for automation, and the ability to design and implement innovative solutions to protect sensitive data and applications in dynamic environments.
Responsibilities:
Implement and maintain data protection tools ensuring optimal configuration and performance.
Develop and manage policies for data loss prevention (DLP) and detection, including scanning and identifying sensitive data across systems.
Monitor and respond to incidents related to data protection, providing "break glass" support to maintain security and availability.
Integrate and optimize data protection tools with other security platforms using APIs, custom scripting, and orchestration frameworks.
Conduct regular assessments of data protection controls to ensure alignment with evolving threats and organizational goals.
Conduct data discovery and classification initiatives, ensuring sensitive information is adequately protected.
Support implementation of context-aware access controls and ensure ongoing compliance with data security policies.
Work with cross functional stakeholders to understand the sensitivity of their data and how they can support the business to fulfill their Data Protection needs.
Collaborate with IT, Privacy, Legal, and Cybersecurity teams to align tactical data protection measures with broader security objectives.
Qualifications:
Experience implementing and managing DLP tools and configuring data protection policies in corporate environments.
Strong scripting and programming skills (e.g., Python, Bash) to automate data protection operations and enhance tool integrations.
Proven ability to integrate security tools using RESTful APIs and customize workflows for scalable, tactical data protection.
Familiarity with endpoint and email security principles, including hands-on experience with protection and monitoring platforms.
Proficiency with infrastructure-as-code tools (e.g., Terraform, Ansible) to automate and standardize security configurations.
Strong understanding of CI/CD pipelines and version control systems (e.g., Git) for deploying and maintaining secure solutions.
Requirements Extensive programming experience in object-oriented languages (e.g., Python, Go, Java) and SQL, with a proven track record in designing maintainable, scalable, and efficient solutions. Robust expertise in the following areas: distributed data processing, data engineering for high-volume data services, or developing scalable data streaming platforms for real-time analytics. Advanced proficiency in cloud and data infrastructure technologies (e.g., AWS, Databricks, Terraform, Apache Spark, Docker) with deep knowledge of development best practices, CI/CD pipelines, and cloud-native deployment. Comprehensive knowledge of RESTful APIs and data integration techniques to enable efficient, secure, and scalable data flow and communication between security systems and user-facing platforms. Strong familiarity with infrastructure-as-code tools such as Terraform or Ansible to automate and standardize security configurations across diverse environments. Hands-on experience with CI/CD pipelines, version control systems (e.g., Git), and modern software development practices to ensure high standards of consistency, quality, and automation in deploying and updating security tools.