I engineer secure multi-cloud data platforms that eliminate enterprise blind spots. By automating compliance workflows and building custom AI agents, I help Fortune 500 organizations turn raw security telemetry into actionable intelligence.
End-to-end data engineering and security solutions for enterprise environments.
Eliminate security blind spots and unify your data landscape. I design multi-cloud data pipelines (AWS, Azure, Snowflake) as the single source of truth, integrating Axonius across your tech stack to discover, reconcile, and feed orphan asset telemetry into your CMDB for 100% infrastructure visibility.
The ATO process shouldn't stall your development. I architect autonomous, pre-production workflows that automatically collect evidence against security controls — whether that's Power Platform, Jira, ServiceNow, or custom-built tooling. The stack adapts to your environment; the outcome is the same: drastically reduced manual overhead and faster secure application time-to-market.
Transform complex telemetry into actionable intelligence and bespoke internal tools. I build secure, data-rich web applications with custom LLM/RAG Copilot agents, predictive ML models, and automated Tableau dashboards so executives can query risk metrics using natural language.
A track record of delivering secure, scalable data solutions for industry leaders.
Architecting the foundational cloud infrastructure and data security strategy for an early-stage health tech DNA testing startup. Defining technical specifications and evaluating technology stacks for secure genomic data handling.
Lead the Cyber Asset Intelligence program within the Cyber Metrics & Reporting team under GRC. Resolve critical CMDB blind spots through Axonius-driven discovery and reconciliation pipelines across 9+ infrastructure domains. Engineered a custom LLM/RAG Copilot agent for natural language security queries. Automated ATO evidence assessments with Power Platform and Jira.
Designed production data pipelines informing security risk posture for Health Information Systems. Built optimized ETL/ELT workflows for security analytics and compliance reporting. Partnered with data science teams to operationalize ML models for anomaly detection.
Developed quantitative risk models and analytics dashboards for enterprise risk management. Applied statistical analysis and machine learning to identify patterns in large-scale security datasets.
Led technical analyses including design optimization studies and thermal data modeling on complex aerospace systems. Streamlined the material selection process, significantly reducing department overhead costs.
A deep, versatile toolkit spanning security, data platforms, and AI.
South Dakota State University · ML Specialization · 2019–2021
University of North Dakota · Aerospace · 2016–2018
Amazon Web Services
Meta
Correlation One · Top 5% of 24,000 applicants · 2021
Kaggle · 2021
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Security data pipelines, cloud platform migrations, compliance automation — let's talk.