I was one of the early hires on to Audubon's new Data & Analytics team with the mission to create an enterprise data architecture from the ground-up to support cross-organizational needs from fundraising to finance, and from policy advocacy to ornithology. I was responsible for vendor selection and implementation for key components such as the data warehouse, ingest engine, pipelining and orchestration tools, and the data warehouse. The data architecture (affectionately referred to as the Data Aviary at Audubon) now hosts nearly 100 datasets, executes dozens of system-to-system integrations and supports the analytic needs of the organization.As dependence on the Data Aviary grew, we needed to expand Audubon's data engineering capacity. I took on the role of Director of Data Engineering. As director, I've integrated the software engineering and data engineering teams, hired 2 additional data engineering staff and manage a team of contractors for various projects. My current focus is on leading my team to best prioritize and implement elegant solutions using best practices from Agile software engineering and data management.

Now a part of Elsevier, Plum Analytics allows researchers to use data to tell the story of their work by demonstrating impact and engagement. In my role as Big Data Architect, I was responsible for setting the technical direction of the platform and leading the development effort. I designed and lead implementation of a platform to improve processing transparency, throughput and data management using a custom process manager, Elastic MapReduce, Spark, AWS Lambda, Kubernetes and Spring Integration - all while reducing cloud computing costs by $500K/year.