Developing tools used to understand, investigate, and reduce cloud spend using generative AI agents and LLMs

Writing Apache Spark code to power Datadog's Cloud Cost Management product. Helping companies understand and optimize their AWS, Azure, and GCP bills.

https://www.datadoghq.com/product/cloud-cost-management/

Reduced processing job latency by 50% saving $800k a year

Lead rearchitecture of AWS EKS container cost monitoring pipeline, transforming it into a multi cloud offering supporting Azure AKS and GCP GKE

Mentored multiple new hires

Promoted early

Saved over 1 million dollars a year through optimization of cloud and Kubernetes resource usage

Developed Terraform modules manage all Apache Spark cloud permissions across Datadog

Mentoring new hire on the team

Developing infrastructure, libraries, and tooling used by data engineers at Datadog to interface with AWS, GCP, and Azure to run Apache Spark and Apache Flink applications on Kubernetes as well as using AWS EMR and GCP Dataproc

Optimized React front end code to improve loading times and responsiveness of components

Refactored python flask api to power a new cross cloud apache spark monitoring website