Lead Information Security Engineer

You desire impactful work.

You’re RGA ready

RGA is a purpose-driven organization working to solve today’s challenges through innovation and collaboration. A Fortune 200 Company and listed among its World’s Most Admired Companies , we’re the only global reinsurance company to focus primarily on life- and health-related solutions. Join our multinational team of intelligent, motivated, and collaborative people, and help us make financial protection accessible to all.

Leads the design and delivery of security data engineering and intelligence capabilities that integrate, correlate, enrich, and operationalize data across security, governance, cloud, application, endpoint, vulnerability, and risk platforms. Builds governed, reusable data products and analytics that improve risk prioritization, remediation effectiveness, control visibility, and measurement of security outcomes. Serves as a hands-on technical lead, leads small and complex cross-functional initiatives, mentors technical staff, and partners with leaders, control owners, remediation teams, Enterprise Data Platform teams, and other stakeholders. Helps define, build, validate, and socialize trusted KPIs, KRIs, control-effectiveness measures, and outcome-based metrics that support clear accountability and measurable risk reduction.

Principle Duties

Leads the design and delivery of complex security data engineering initiatives and small cross-functional project teams, providing technical direction from solution design through implementation and operational ownership.

Ingests and integrates data from security, governance, cloud, application, endpoint, vulnerability, identity, and risk platforms using scalable data pipelines, applications, APIs, and automation.

Deduplicates, correlates, and enriches security findings with asset, ownership, business, control, and risk context to produce actionable intelligence.

Designs and delivers governed security data products through RGA’s Enterprise Data Platform, using Snowflake and enterprise data-engineering patterns to make security information reusable, trusted, and accessible.

Develops and optimizes Snowflake data models, SQL transformations, queries, and compute patterns while managing data quality, performance, access, traceability, and cost.

Partners with Enterprise Data Platform, Data Governance, and security teams to establish sustainable ingestion, transformation, role-based access, lineage, metadata, data-quality, and lifecycle practices.

Co-develops KPIs, KRIs, control-effectiveness measures, thresholds, targets, and supporting calculation methodologies aligned with security strategy, risk objectives, and technical standards.

Establishes metric governance through documented definitions, authoritative data sources, ownership, data-quality checks, refresh cadence, version control, and traceability to underlying risks, controls, and remediation workflows.

Socializes metrics with leaders, control owners, and remediation teams by translating technical results into clear risk narratives, validating definitions and assumptions, and connecting executive indicators to accountable teams and actions.

Develops tool-agnostic dashboards, scorecards, reporting capabilities, and reusable services with drill-through from leadership indicators to supporting assets, controls, findings, and remediation work.

Identifies trends, systemic risks, concentrations of exposure, control gaps, and remediation opportunities, and provides clear recommendations to technical teams and leadership.

Builds strong data foundations for security automation and future AI-enabled and Model Context Protocol-based capabilities.

Technically mentors associates, establishes engineering standards, guides design and peer reviews, and provides training and knowledge sharing as required.

Evaluates new security, data, and analytics technologies and recommends solutions that maximize business value while reducing manual effort and unnecessary vendor dependency.

Communicates architecture, tradeoffs, delivery status, risks, and recommendations clearly to technical teams, leaders, and business stakeholders.

Success Measures

Security data from multiple platforms is consistently integrated, normalized, enriched, governed, and available for decision-making.

Leaders, control owners, and remediation teams share trusted definitions for KPIs, KRIs, controls, thresholds, targets, and ownership, with clear links to prioritized actions.

Executive indicators provide concise risk and performance narratives with drill-through to the teams, assets, controls, and remediation work driving the result.

Security data is delivered through reusable Enterprise Data Platform and Snowflake data products rather than isolated pipelines, manual extracts, or tool-specific reporting.

Manual integration and reporting effort is reduced through scalable automation, reusable engineering patterns, and documented ownership.

RGA can better quantify material exposure, control coverage, remediation effectiveness, security debt, and the business value of security initiatives.

Small team projects are delivered with strong technical direction, stakeholder alignment, sustainable ownership, and measurable outcomes.

Education

Required

Bachelor’s degree in Arts/Sciences (BA/BS) or equivalent experience

Preferred

• •Master’s degree in Arts/Sciences (MA/MS) or relevant professional industry certification
• •CISSP, CISA, CCSP, CGRC, Comptia CASP+, OSCP, CEH Certifications

Work Experience

Required

• •6+ years of experience in security engineering, information systems, data engineering, security analytics, application development, or a closely related discipline, including significant hands-on security technical delivery.
• •Demonstrated experience leading technical projects or small project teams, guiding solution design, mentoring others, and driving work through delivery.

Preferred

Experience managing and developing security data products, analytics, reporting, or metrics within a governed enterprise data environment.

Preferred Technical Experience

Experience with Snowflake, dbt, Airflow, Atlan, Power BI, Git-based development workflows, infrastructure as code, CI/CD, containers, or serverless application patterns.

Experience with security platforms such as Wiz, GitHub Advanced Security, GitGuardian, CrowdStrike, Tenable, Nucleus, LogicGate, or comparable technologies.

Knowledge of exposure management, vulnerability prioritization, risk-based remediation, security program measurement, and control-effectiveness reporting.

Experience with AI-enabled integrations, automation, or Model Context Protocol.

Relevant cloud, security, data engineering, analytics, or architecture certifications.

Skills and Abilities

Required

Strong information security knowledge and the ability to work with vulnerability, exposure, cloud, application, endpoint, identity, governance, and control data.

Experience defining and operationalizing KPIs, KRIs, control measures, and outcome-based metrics, including calculation logic, thresholds, targets, ownership, and validation.

Working knowledge of governed data-product practices, including role-based access, lineage, metadata, data quality, ownership, and secure data sharing.

Experience with security analytics, business intelligence, dashboard development, data visualization, and executive or operational reporting.

Advanced hands-on skill with Python, SQL, APIs, data modeling, databases, and automated data pipelines.

Experience building analytical models, pipelines, or data products on Snowflake, an enterprise data platform, or a comparable cloud data ecosystem.

Experience designing, developing, deploying, and operating applications or data services in AWS or another major cloud platform.

Advanced oral and written communication skills, including the ability to explain complex technical and risk concept