ML Infrastructure

* Created a mechanism to populate Opensearch clusters based on DynamoDB table exports using Kinesis and Glue for new cluster onboardings and emergency recovery scenarios

* Onboarded Sagemaker machine learning models for use in an external business annual revenue prediction workflow, resulting in a 50% increase in revenue coverage

* Augmented API service to return additional business intelligence signals, enabling the detection of $260 million worth of fraudulent transactions per year

* Orchestrated a complete migration of AWS services from eu-west-1 to eu-south-2, resulting in a 35% decrease in annual compute and storage spend in our EU region

* Added record deduplication functionality to PySpark ETL pipeline, reducing redundant records by 40% and subsequent ML matching workflow runtime by 80%

DeltaV Product Improvements

* Implemented a bulk edit mechanism using WinForms to populate or configure DeltaV modules from Excel, reducing manual entry effort by 90%

* Designed a version control mechanism to track and rollback DeltaV system configuration changes using Git

Built a data analytics reporting pipeline for existing internal ML infrastructure

Full-Stack internal tool built using React and AWS Lambda