Highly motivated software engineer with a passion for performance optimization in system architecture and user-facing solutions, and solving the complex problems therein.
Recently (2024) single-handedly wrote a network traffic engine/sniffer/dissector in Rust for an in-house AI platform.
Responsible for redesigning and reimplementing business critical backend systems resulting in significant performance uplift (5x).
•
High-performance python data pipeline architecture, maintenance, and feature improvement.
•
Designed data-driven workflows using AWS Step Functions, SNS, and SQS, and Celery to deliver efficiency gains for high-impact and industry leading data extraction.
•
Jenkins Pipeline Design
•
Helm chart configuration to manage, deploy, scale, and create new services within Kubernetes clusters within EKS.
•
REST API efficiency gains with high-performance route creation to increase throughput throughout data pipeline.
•
Drastically increased internal OCR pipeline efficiency by parallelizing heavy workloads, resulting in a 20% performance uplift. Fine-tuning of scaling metrics allowed for 30% throughput improvement.
•
Docker image creation, fine-tuning and deployment on AWS Lambda and ECS.
•
Increase data ingestion capabilities with leveraging Amazon SES for email reception and data extraction.
•
Improve end-user experience on internal company tooling using React.
•
Create, design, use, and improve data-driven services using internally-designed api calls Postgres and MongoDB.
•
Database schema design and improvement for Postgres using internally managed Alembic versioning.
•
Designed, implemented, and released high-performance and feature complete data pipeline leveraging AWS lambda, SNS, SQS and Step Functions.
•
Internal and External facing API creation and design for performant data ingestion and delivery.
