I am specialized in backend cloud engineering in AWS/GCP, particularly microservice architecture in Go, Java, and several other languages. I have more than 6 years' experience in this role.
At Model-Prime, I helped design and build the Core Services platform which handles ingest, parsing, storage, and searching of robotics log data. I pride myself in designing and implementing REST APIs using well-tested, idiomatic, extensible Go code. This stack involved AWS ECS (Fargate), Postgres/RDS, Lambda, SQS, and other services. I also gained experience using Apache Airflow in Python. GitLab Pipelines for deployment.
At Lytics, I managed a different sort of data ingest pipeline, this time processing real-time streaming event data into meaningful customer profiles. We used GCP's Pub/Sub to receive messages and process them using a managed Kubernetes cluster, writing to Google BigTable as a graph database. Additionally, we developed APIs (also deployed in GKE) for retrieving and performing operations on these profiles. This role was Go-focused.
Before that, I worked for a year at Nike Digital Engineering on performing a cloud migration for their point-of-sale app (known as Assist) so that it would be able to function independently of a store server. We used an AWS stack in Java and NodeJS, usually DynamoDB for persistence, to build cloud microservices that were highly interoperative not only with each other, but also with services managed by other teams at Nike.More...