I help teams build observability-first data platforms and production-ready ML systems that reliably turn data into business outcomes. I focus on pragmatic architecture, clear decision records, and shipping with measurable impact.
15+ years of work across data engineering, analytics platforms, and business analytics.
Progression from foundational database and ETL work through cloud-based platforms and analytics enablement,
with recent focus on applied AI and GenAI. Currently pursuing an MBA.
Areas of Focus
Data engineering, ETL, and foundational infrastructure
Selected architectural and product decisions made while building and scaling data systems.
Feb 2026
Choosing Columnar Storage (Parquet) Over Row-Based Formats for Analytics Workloads
Our analytics platform was processing increasingly large datasets (growing from 500GB to 5TB annually) with queries focusing on aggregations across specific columns rather than retrieving full records. Traditional row-based storage (CSV, JSON) resulted in slow query performance, high storage costs, and inefficient data scanning. Query times for typical analytics operations ranged from 2-5 minutes, impacting business user productivity and limiting ad-hoc analysis capabilities.
Problems I Solve
Scale systems without adding complexity
Trade-offs between consistency and availability
Modernize and maintain legacy codebases
Design durable, well-versioned APIs
Build teams that ship reliably
Treat technical debt as a strategic investment
Let's Work Together
Seeking technical leadership, architecture guidance, or disciplined documentation? Let's talk.