Essow Gnassingbe

I’m a Software Engineer at Goldman Sachs specializing in high-throughput distributed systems, data pipelines, and financial technology platforms processing hundreds of millions of records daily. I enjoy turning complex, legacy systems into reliable, scalable pipelines that engineers can confidently operate.

In my role, I engineered a distributed Java data processing pipeline executing ~300M risk calculations across ~60K tradable assets daily. I built and modernized systems for risk discovery/classification and valuation attribution, migrating infrastructure to Snowflake to improve maintainability and enable scalable cloud-based processing.

I also architected messaging infrastructure for decoupled microservices using RabbitMQ, with deployments via Kubernetes and Terraform to improve fault tolerance and reduce infrastructure overhead. Alongside that, I developed full-stack internal tooling with React and Spring Boot for reconciliation and automated attribution reporting backed by MongoDB and Snowflake.

Beyond core backend work, I create high-volume REST APIs and backend services to support mission-critical financial pipelines. I’ve also built an LLM-powered agent using Google ADK and Devin AI to investigate production data quality issues and accelerate time-to-diagnosis for on-call engineers.