Principal Security Engineer, Security Data & Reporting

The Principal Security Engineer provides technical leadership and hands-on engineering for security data platforms, reporting applications, and analytics that help operational teams and leadership understand enterprise security posture and make informed risk decisions. The role designs, builds, and operates automated data pipelines, repeatable security metric calculations, and reporting solutions that turn data from multiple systems into accurate, traceable, and actionable information. Working with security subject matter experts, engineering teams, and program leadership, this engineer translates complex measurement needs into secure, reliable, and maintainable solutions. The role resolves integration and data-quality challenges, applies sound architectural judgment, and independently delivers complex engineering initiatives. It develops and integrates AI-enabled capabilities to improve analysis and reporting, with appropriate validation, human review, and data-access controls. The Principal Security Engineer owns solutions from design through deployment, ongoing operation, and continuous improvement, while providing technical guidance and strengthening shared engineering practices. KEY RESPONSIBILITIES Security Data Integration and Engineering Designs, builds, and maintains automated integrations that collect data from security tools, enterprise applications, APIs, databases, and other source systems. Establishes centralized data structures and ingestion workflows that support reliable security measurement, historical analysis, and reporting, with appropriate validation, error handling, monitoring, and recovery capabilities. Partners with security and engineering teams to assess source-system coverage, data availability, refresh requirements, integration dependencies, and ownership. Replaces manual data collection with supported automation while maintaining data quality, validation, and clear accountability. Evolves the integration architecture to accommodate additional data sources, metrics, and reporting needs while balancing near-term delivery with long-term maintainability. Data Modeling and Metric Implementation Translates security measurement requirements into documented data models, transformation logic, and repeatable metric calculations. Normalizes and reconciles data across systems, addressing inconsistent definitions, duplicate records, incomplete coverage, and differences in reporting periods. Implements and validates metric calculations, baselines, and trends using definitions and targets agreed with security subject matter experts and program leadership. Maintains traceability from reported metrics to source data, calculation logic, and applicable scope; preserves historical results and manages calculation changes so reporting remains explainable and comparable over time. Investigates and communicates data-quality issues, measurement limitations, and assumptions, recommending improvements that strengthen the accuracy and interpretation of security reporting. Dashboard and Reporting Application Development Develops and maintains dashboards and reporting applications using Oracle APEX or comparable technologies. Translates leadership and operational reporting needs into clear, usable views, incorporating stakeholder feedback and perspectives from different reporting audiences. Provides appropriate drill-down capabilities so users can investigate results and understand the factors contributing to changes in security posture. Builds data submission, validation, review, and publication workflows where automated source integration is not yet available. Evaluates whether visualizations accurately communicate the intended security outcomes and improves reporting usability, performance, and maintainability through iterative development. Automation and AI-Enabled Analytics Designs, develops, and integrates AI-enabled features into security data platforms, dashboards, and reporting workflows. Evaluates and applies generative AI, large language models, and other analytical techniques to support natural-language exploration, contextual analysis, reporting automation, anomaly detection, and forecasting where appropriate. Connects AI-enabled functionality to authoritative security data and metric definitions, maintaining source traceability and enforcing audience-specific access controls. Establishes evaluation and validation methods to assess accuracy, reliability, and usefulness, with appropriate human review of generated interpretations and recommendations. Monitors and improves AI-enabled features as data, models, and requirements evolve, using defined measures to assess effectiveness and guide further investment. Security, Permissions, and Access Controls Designs and implements role-based access and least-privilege permissions for data contributors, reviewers, administrators, and reporting audiences. Partners with identity, infrastructure, and security teams to integrate authentication and authorization with enterprise standards. Applies secure credential handling and appropriate controls to protect sensitive security data. Implements logging and auditability for relevant data changes, administrative actions, and reporting workflows. Incorporates security requirements into application design, development, testing, and operation, including AI-enabled functionality. Reliability and Operational Ownership Owns developed integrations and reporting applications through deployment, ongoing operation, maintenance, and continuous improvement. Establishes testing, version control, deployment practices, and technical documentation that support reliable changes and maintainable solutions. Monitors data freshness, processing failures, completeness, and reporting availability; investigates issues using structured analysis and coordinates resolution with relevant teams. Supports scheduled reporting and leadership review cycles by validating readiness, addressing issues within agreed delivery windows, and communicating delivery risks. Develops runbooks and recovery procedures, coordinates database, hosting, and platform requirements, and incorporates operational lessons into engineering practices. Technical Leadership and Collaboration Independently scopes and delivers complex engineering initiatives, identifies dependencies, estimates effort, and communicates progress, risks, and tradeoffs. Works with security subject matter experts to understand controls, operational processes, and source data; identifies gaps in requirements, data coverage, and proposed solutions. Builds effective partnerships across security, engineering, infrastructure, and program teams, aligning implementation plans with stakeholder needs and establishing clear ownership and delivery expectations. Applies sound technical judgment to resolve ambiguity and adjust plans as priorities or constraints change; escalates unresolved issues with an assessment of impact and recommended options. Expands relevant technical knowledge, mentors colleagues, documents and shares solutions, and contributes to shared engineering practices. MINIMUM QUALIFICATIONS Education and Experience One of the following: 11 years of experience in IT security, developing security reporting solutions, such as cloud, endpoint, or logging; vulnerability and risk assessment; identity and access management; compliance; or a related field. OR Bachelor’s degree in Computer Science, Information Technology, Computer Security, Engineering, or a related field, and 7 years of experience in IT security, such as cloud, endpoint, or logging; vulnerability and risk assessment; identity and access management; compliance; or a related field. OR Master’s degree in Computer Science, Information Technology, Computer Security, Engineering, or a related field, and 5 years of experience in IT security, such as cloud, endpoint, or logging; vulnerability and risk assessment; identity and access management; compliance; or a related field. Techn