I'm a seasoned developer with nearly two decades of experience building websites, high throughput services, and backend data infrastructure. Over the fifteen years, I've focused on big data analytics, catalog systems, and high-throughput data access.I currently focus on the catalog ecosystem for Iceberg tables. As one of the founding engineers of the Apache Polaris project, I helped deliver a full-featured, enterprise ready reference implementation of the Iceberg REST catalog and launched Snowflake's managed Open Catalog. I'm also a contributor to the open source Marquez project and a TSC member of the open source OpenLineage standard and a contributor to various OpenLineage integration projects. I've led multiple teams, including Amazon's biggest clickstream data ingestion and analytics system and their primary website experimentation platform. The experimentation platform was used by nearly every team within Amazon retail to run live experiments on one of the largest websites in the world. We processed billions of sessions per day to quantify the real effect code changes had on latency, repeat visits, and orders. The clickstream data platform was used by every analytics team within Amazon retail to track customer activities and powered core systems, such as recommendations, advertising, and similarities.At Cruise, I built high-throughput data serving and catalog services that provide access to petabytes of road and simulation data for road data analysis, batch analytics and ML, and real time metrics calculation.I have a passion for team and company culture - especially where we can increase operational excellence and rapid development. I've advised and mentored developers across multiple companies, enhancing technical expertise and developing engineers who know how to figure out what to build.I love to explore. I am constantly learning and I'm always curious. I have a passion for making complex problems simple and eradicating boilerplate and mundane tasks. I believe innovators should be able to create and dream big without being encumbered by the tedious and dreary necessities of unnecessary complexity. I love making big data simple and making rapid development and experimentation the norm. I spent the better part of my career on the JVM, working in Java, Groovy, and Scala, managing large-scale, optimized services using standard JVM tools. I also spent years off the JVM, building services in Python, and Go. Regardless of the language, I deliver operationally solid systems, instrumented for observability, efficiency, and debuggability.