Security DLP Engineer

Your opportunity

• Ensuring integrity and security of information across multiple platforms for unstructured and structured data within on-premises and cloud-based infrastructure.
• Develop, engineer and automate quality monitoring of unstructured and structured data to ensure accurate response rules based on corporate security and compliance policies.
• Provide risk-mitigation recommendations to Schwab Cyber Security; build (or review and validate) requirements to maintain or enhance technical and operational controls that ensure the protection of sensitive data.
• Continually evaluate effectiveness and efficiency of data protection systems as needed in order to tune security configurations to reduce false positive events while improving detection of high quality, quantifiable and measurable risk events.
• In the scope of the tool set be able to gather requirements, design, test, implement, operate, solve and perform root cause analysis of problems.
• Deliver new and improved data protection capabilities, analytics, visualizations, reporting, and impactful, valuable, risk intelligence in short, sprint-like outcomes.
• Collaborate with enterprise and security architecture, governance, risk, onboarding, and production support teams while building and maintaining durable data security solutions.
• Proven thought leadership with Python, C#, .Net MVC, RESTFul Methodologies, Git, and Continuous Integration/Deployment tooling.
• Evaluate and prioritize workstreams for efficient delivery via an Agile methodology.
• Coach, mentor and develop less experienced colleagues.

What you have

• Expertise in source control, unit testing, and agile methodologies is paramount.
• Bachelor of Science in Information Technology, Information Security, Computer Science or related is preferred.
• 3-5 years of enterprise-level system administration experience, supporting multiple DLP technologies that are subject to high levels of audit and regulatory oversight, is required.
• Fundamental skillset utilizing EDM/IDMs and compiling complex Regex’s to identify different levels of data classification within structured and unstructured data elements.
• Understanding and utilization of data classification/labeling techniques in a complex environment.
• Strong functional familiarity with the following: CASB, Proxy, Network DLP solutions, Google Cloud, AWS, endpoint DLP. DNS and TCP/IP Internet and networking technologies within large, distributed environments.
• Ability to configure, design and implement data protection, encryption in transit, encryption at rest, cloud KMS, Identity Aware Proxy, cloud DLP, cloud security compliance and handle security operations within a cloud solution environment.
• Development and scripting experience in Cloud Service Provider IaaS environments such as AWS, Azure, and GCP