Job Description

Location & Remote Flexibility
While this job posting lists a specific state to meet platform requirements, this is a 100% nationwide remote position We encourage qualified candidates located anywhere within the United States to apply!

Senior Security Data Analyst

Service Scope:

○ Establish and monitor the department’s primary data repositories, ensuring datasets remain authoritative, accurate, and structured for long-term usability.

○ Proactively audit complex security datasets to identify, investigate, and correct data inconsistencies, gaps, or logic errors across core tracking systems.

○ Design and execute structured data normalization workflows, blending disparate data streams from various enterprise tools (e.g., Asana, AODocs, ServiceNow, internal sheets) into a unified architecture.

○ Document strict data lineage, tagging standards, and processing rules to provide complete audit traceability and compliance validation for all reported metrics.

○ Design, build, and optimize enterprise-level security dashboards and performance tracking views using data visualization tools (e.g., Tableau, Looker Studio).

○ Synthesize complex data trends, operational velocities, and technical metrics into concise, data-backed summaries and presentation-ready content for senior executive leadership.

○ Compile, validate, and organize historical data packages and KPI trends to feed directly into departmental Monthly Readouts and Quarterly Business Reviews (QBRs).

○ Execute systematic data verification and compliance auditing processes to support internal controls oversight and risk management frameworks.

○ Manage, prioritize, and execute incoming ad-hoc data requests and deep-dive analytical queries from across the broader physical security organization within established turnaround windows.

○ Collaborate logistically with Project Managers, Coordinators, and Technical Writers to gather accurate data inputs, validate cross-functional dependencies, and ensure metric integrity.

○ Implement and support AI-driven data analysis workflows, utilizing modern generative AI tools and scripts to accelerate data cleansing, categorization, and pattern recognition.

○ Identify opportunities to automate manual data collection and reporting mechanics, continuously improving data pipeline efficiency and reducing time-to-insight.

○ Build, deploy, or maintain custom low-code/no-code applications and automated workflows using Google AppSheet, extending applications with custom scripting (e.g., Google Apps Script, Python) as required to facilitate webhooks, automated multi-system syncs, or automated trigger-based notifications.