Milestone Technologies is looking for a Senior Security Data Analyst to support data-driven decision-making on the team. The successful candidate must have experience in data analysis, the ability to think analytically, and the skills to optimize our delivery process. The data analyst must be proactive, results-driven, and detail-oriented; the candidate must thrive in a team environment and be able to work independently. Service Scope: i. Establish and monitor the department’s primary data repositories, ensuring datasets remain authoritative, accurate, and structured for long-term usability. ii. Proactively audit complex security datasets to identify, investigate, and correct data inconsistencies, gaps, or logic errors across core tracking systems. iii. 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. iv. Document strict data lineage, tagging standards, and processing rules to provide complete audit traceability and compliance validation for all reported metrics. v. Design, build, and optimize enterprise-level security dashboards and performance tracking views using data visualization tools (e.g., Tableau, Looker Studio). vi. Synthesize complex data trends, operational velocities, and technical metrics into concise, databacked summaries and presentation-ready content for senior executive leadership. vii. Compile, validate, and organize historical data packages and KPI trends to feed directly into departmental Monthly Readouts and Quarterly Business Reviews (QBRs). viii. Execute systematic data verification and compliance auditing processes to support internal controls oversight and risk management frameworks. ix. 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. x. Collaborate logistically with Project Managers, Coordinators, and Technical Writers to gather accurate data inputs, validate cross-functional dependencies, and ensure metric integrity. xi. Implement and support AI-driven data analysis workflows, utilizing modern generative AI tools and scripts to accelerate data cleansing, categorization, and pattern recognition. xii. Identify opportunities to automate manual data collection and reporting mechanics, continuously improving data pipeline efficiency and reducing timeto-insight. xiii. Build, deploy, or maintain custom low-code/nocode applications and automated workflows using Google AppSheet, extending applications with custom scripting (e.g., Google Apps Script, Python) as required to facilitate webhooks, automated multisystem syncs, or automated trigger-based notifications. Originally posted on Himalayas