As a member of the data ingest team, I am responsible for the development and maintenance of a highly available, distributed, and latency sensitive data ingest pipeline with services written in modern C++ and Go. I was able to orchestrate collaboration across teams to drive impactful changes and able to independently identify and execute on high impact opportunities.

• Modeled and simulated interactions between backend services - lead to the discovery of a configuration optimization that reduced data latency by 16% and unit cost by 20%.

• Designed and drove the development of a feature (inspired by CPU out of order execution) that addressed Kafka head of line queue blocking in a key Go service.

• Delivered custom transformations in modern C++ that transformed OpenTelemetry protobufs to a proprietary format to power a first class Kubernetes observability product.

• Maintained Go based control plane and GQL API to reflect changes in data pipeline capabilities.

• Worked on improvements to the RDS export to S3 service.

• Built a more accurate system to track export progress

• Worked on implementing a new database partitioning method to improve export speed

• Designed and implemented rds export api to enable customers to exclude objects from rds database exports.

• Reduced wasted resources and customer cost with smarter validation logic preventing empty exports.

• Refactored internal dynamoDB schema and EMR microservice to enable the combination of export-only and exclude parameters allowing for reduced CLI query size saving up to 4MB per query.

• Led initiative to evaluate interoperability of various low level networking libraries in Rust.

• Implemented ARP probing and IP packet forwarding achieving speeds of up to 4000mb/s as a part of a

research project evaluating the viability of a hostname based network egress filter.