•Architected an event processing pipeline using Azure Queues and developed a back-end service (Go) to ingest and write thousands of audit events to durable storage per second
•Developed a back-end service (Go) to monitor real-time data replication from primary to secondary storage, achieving a 75% reduction in replication failure alert latency, from 1 hour to 15 minutes
•Refactored AI model runner deployments to more efficiently select jobs for execution, increasing the model execution pipeline resource efficiency by 50%
•Implemented a new Azure-based backup system for GPv2 storage accounts, overcoming the 125x cost barrier associated with using the existing GPv1 backup system
•Identified redundant labels annotated by Epic’s distributed logging library (Typescript), reducing the cost of storing log metadata by 18%
•Provisioned and configured storage resources using IaC (Terraform) for the migration of Epic’s genetic variant dataset exceeding 100TB
•Advised on the Azure CosmosDB (NoSQL) data model for Epic’s URL shortening and redeeming service handling millions of requests per day
•Led meetings with Azure product teams to evaluate beta features, saving 100 hours of development time by adopting upcoming first-party features
•Improved data security by developing a core encryption library (Go) to standardize and consolidate implementations requiring encryption using the XChaCha20-Poly1305 cipher
•Enhanced GitLab CI pipelines to warn and block builds using outdated versions of Go, ensuring projects stay up to date with current releases
