Lafayette, Louisiana, United States
I build the data infrastructure that institutional financial clients depend on to operate; pipelines that run reliably, at scale, every day. Over the past 5 years at Code Willing, I've grown from building foundational ETL pipelines to owning the architecture of a distributed data platform that processes 74,000+ jobs and 401+ GB of data daily for institutional financial clients. I was trusted as the sole platform architect on two successive greenfield initiatives - making the core technical decisions, writing the documentation that shaped engineering direction across the organization, and serving as the escalation point when production incidents needed to be diagnosed and communicated directly to clients. My work sits at the intersection of distributed systems, event-driven architecture, and lakehouse modernization. I care about building things that scale cleanly, fail gracefully, and don't require heroics to maintain. Outside of work I'm drawn to understanding the fundamentals beneath my stack and am currently working through computer architecture from the ground up for fun
- Own platform architecture and technical roadmap as the entry point of the data pipeline — architectural decisions have direct downstream impact across multiple consuming engineering teams supporting institutional financial clients. - Lead cross-functional delivery across a 5-person engineering team and a 4-person international follow-the-sun team, maintaining platform reliability standards required by institutional financial operations. - Maintain and evolve CI/CD pipelines to support continuous delivery across microservices, ensuring independent deployability and minimizing risk across production releases.
- Architected event-driven ingestion platform integrating APIs, S3, and file-based vendors — outperformed client's legacy system on 76% of 60,770 benchmarked files; legacy ran 5+ minutes slower on 20,800+ files. - Designed distributed workflows using Redpanda, Airflow, and DolphinScheduler supporting 19,600+ files/day (253 GB/day) with strong fault tolerance and SLA reliability. - Led migration of relational data from PostgreSQL to Apache Iceberg lakehouse on AWS S3, enabling point-in-time querying for backtest trading strategies. - Integrated AWS Secrets Manager to centralize and secure credential management across platform services. - Co-built an internal Python SDK for launching and managing distributed compute clusters in Apache Spark and Ray — contributed architecture review, quality assurance, and recalibration; demoed to clients who expressed interest in it as a standalone product. - Served as primary technical escalation for production incidents — led root cause analysis and communicated findings and remediation plans directly to institutional clients. - Built internal frameworks standardizing pipeline patterns; conducted PR reviews, mentored engineers, and led design sessions.
- Developed scalable ETL pipelines and APIs supporting analytics and operational workloads for institutional financial clients. - Improved database performance through query tuning and schema optimization across PostgreSQL and MySQL. - Established architectural foundations for the transition to distributed data architecture. - Contributed to CI/CD pipeline setup and deployment practices, enabling consistent and repeatable delivery across the team's growing service footprint.