Oak Ridge, Tennessee, United States
I am a Data Solutions Architect and Technical Lead specializing in enterprise data platforms, governance, and AI-ready architectures within regulated environments. I lead cross-organizational engineering efforts spanning multiple companies, establishing architecture standards, governance patterns, and scalable data platform solutions. My work focuses on turning fragmented, high-friction data ecosystems into structured, observable, and reusable platforms. I believe strong data platforms are built through observability, alignment, and pragmatic governance—not rigid control at ingestion. My approach emphasizes scalable patterns, domain ownership, and enabling teams to move faster with better data. Primary focus areas include Databricks (Lakehouse, Unity Catalog), Spark, SQL-first architecture, and cloud-native data engineering. Prior to my current role, I built and modernized data platforms across startups and enterprise environments, and served 20+ years in the military leading teams in high-pressure operational settings.
Rapidly promoted to Data Solutions Architect within 12 months; currently serve as Contractor Technical Lead supporting a federal data and AI office. Lead technical direction across multiple contracting organizations, establishing architecture standards, governance patterns, and engineering best practices. Drive enterprise data platform modernization using Databricks Lakehouse (Unity Catalog, Spark), aligning cross-team development with scalable and governed design patterns. Rearchitected high-priority solutions within 60 days of hire, introducing SQL-first architecture and reducing delivery timelines by approximately three months. Facilitate cross-functional technical decision-making and resolve complex system challenges through structured design sessions and stakeholder alignment. Design reusable platform patterns for ingestion, transformation, and governance, improving scalability and consistency across teams. Mentor engineers and technical leads through office hours, design reviews, and architecture guidance.
Engineered scalable data pipelines ingesting enterprise data from APIs, databases, and flat files into cloud data platforms. Led modernization of legacy pipelines from Python 2.7 to Python 3.9, significantly improving reliability and maintainability. Established Docker-based deployment standards and version control practices for ETL systems. Built reusable connector frameworks accelerating onboarding of new data sources. Partnered with enterprise clients to design ingestion and reporting architectures for complex datasets.
Mission-Critical Data: Executed high-integrity data cleaning and ingestion processes on PostgreSQL databases to enhance analytics for Social Determinants of Health.
Strategic Advisory: Designed Snowflake schemas and data models while teaching DataOps to enterprise clients; implemented dbt and conducted TCO analysis for cloud data platforms.