I help teams learn and use AWS technologies. My primary focus area is Amazon DynamoDB, where I've worked with all kinds of clients, from product companies to consultancies; from government agencies to publicly-traded enterprises. I can provide professional training to quickly level up your entire team, or I can help review or design a data model for an important project. I'm the author of The DynamoDB Book, a comprehensive guide to data modeling with DynamoDB that has been endorsed by AWS for use by its internal developers. Additionally, I've been recognized as an AWS Data Hero for my work with DynamoDB in the AWS community.In addition to DynamoDB, I provide assistance with all sorts of AWS services, particularly those used in Serverless architectures (Lambda, API Gateway, Step Functions, SQS, SNS, Kinesis, etc.).

In this role, I served as an Engineering Manager and Team Lead for the Platform team. We focused on building out the commercial offerings for Serverless, Inc., which included an opinionated CI/CD deployment system, a monitoring pipeline and associated plugins for the Serverless Framework. My responsibilities included assisting with long-term planning, designing key systems, coordinating bi-weekly sprints, and managing a team of four backend engineers. During this time, we experienced our first paying customers for a Serverless, Inc. product and saw strong, consistent growth in product maturity.

In this role, I planned and coordinated all Growth Team activities for Serverless, Inc. This included regular content releases, SEO planning, community engagement, conference talks, and email newsletters. During this period, Serverless, Inc. had its strongest period of growth as measured by website traffic, Framework usage, and newsletter signups.I initially was hired as a Data Engineer on the Growth Team. During this time, I implemented tracking of all key metrics and significantly increased our engagement with the developer community through blog posts and forum discussion.

At Hudl, I was a founding member of the Data Engineering team. We were tasked with consolidating data from many sources, including production data in microservices, analytic data from logs, and exported data from third-party services. Our small team built reliable, maintainable data pipelines and the associated query infrastructure to democratize data access across Hudl's 500+ employees. In this role, we used Amazon Redshift, S3, EMR, Lambda, Kinesis, and a host of other technologies.

In this role, I worked on mergers & acquisitions, public company filings, credit agreements, and other business legal needs both for public and private companies.