Senior Data Security Engineer

The Senior Data Security Engineer will help build and operationalize a Data Security Posture Management capability across on premises, cloud, Software as a Service, and hybrid environments. This role will partner with engineering teams to design, develop, implement, and operate solutions that protect sensitive data, reduce risk, improve visibility, and support governance, monitoring, and remediation workflows. Responsibilities Engineer and operate Data Security Posture Management capabilities that continuously discover, inventory, classify, assess, monitor, and protect sensitive data across structured and unstructured data stores. Onboard data sources across databases, data warehouses, data lakes, object stores, file platforms, Software as a Service applications, and cloud services through connectors, scanners, application programming interfaces, and customer side components. Design and build secure integrations between Data Security Posture Management platforms and enterprise services, including data catalogs, identity and access management, configuration management, security monitoring, incident response, ticketing, reporting, and downstream control systems. Develop Python services, scripts, and automation for source onboarding, metadata enrichment, scan orchestration, evidence capture, finding normalization, risk scoring, workflow integration, and remediation. Correlate data sensitivity, ownership, location, lineage, permissions, identity context, configuration, exposure, and activity signals to identify and prioritize material data risks. Configure and tune discovery, classification, policies, analytics, alerting, dashboards, and workflows while measuring classifier quality, coverage, false positives, and control effectiveness. Implement and validate least privilege, Zero Trust, encryption, masking, tokenization, labeling, retention, and other data protection controls with platform teams. Translate findings into remediation actions, automate response patterns, and track risks, exceptions, ownership, evidence, and closure. Support security architecture reviews by documenting deployment footprints, data flows, trust boundaries, access models, encryption, logging, software components, and control evidence. Build observability for platform availability, connector health, scan performance, data freshness, coverage, finding quality, and integration reliability. Participate in design reviews, code reviews, testing, release management, Agile ceremonies, operational readiness activities, documentation, and knowledge sharing. Partner with governance, privacy, compliance, security operations, application, cloud, and data owners to convert technical insights into business relevant risk improvements. Collaborate with peer engineers to establish reusable patterns, review designs and code, and resolve technical risks and dependencies. Qualifications Required Qualifications Seven or more years of experience in cybersecurity, data security, security engineering, data engineering, cloud security, or a related field. Strong understanding of Data Security Posture Management concepts and data centric security practices. Experience with structured and unstructured data environments and modern data architectures. Strong Python development skills and application programming interface integration experience. Experience integrating enterprise platforms using application programming interfaces, event driven architectures, queues, or streaming technologies. Knowledge of identity and access management, least privilege, encryption, logging, secrets management, and network security. Experience with Linux, Git, continuous integration and continuous delivery, automated testing, containers, and infrastructure automation. Strong troubleshooting skills across applications, operating systems, networks, cloud services, identities, and data sources. Understanding of data classification methodologies, privacy requirements, regulatory obligations, and risk based controls. Ability to create technical designs, operational procedures, metrics, and risk communications for technical and business audiences. Understanding of secure and governed artificial intelligence practices throughout the technology lifecycle. Preferred Qualifications Experience with Data Security Posture Management, data discovery, data classification, data catalog, data loss prevention, insider risk, or data access governance solutions. Experience with Microsoft Purview, BigID, Varonis, Cyera, Securiti, or similar technologies. Experience with Azure, Amazon Web Services, Google Cloud, MongoDB, relational databases, data warehouses, data lakes, or lakehouse platforms. Experience with Kubernetes, Docker, Terraform, Ansible, Kafka, Jenkins, Flux, Grafana, Loki, or Splunk. Knowledge of security monitoring, automation and response platforms, configuration management databases, data lineage, identity and access management, cryptography, masking, retention, and secure deletion solutions. Familiarity with NIST guidance, Zero Trust principles, cloud security baselines, and security frameworks used in regulated environments. Experience supporting security reviews, proof of concept initiatives, technology onboarding efforts, or production readiness assessments. Skills and Requirements – add details here #J-18808-Ljbffr 247Hire