• Managed core backend services in Java for trading and risk systems, scaling the order processing pipeline to handle 18,000 requests per minute and keeping end-to-end trade-acknowledgement latency below 120 ms during market hours.

• Programmed React micro-frontends for portfolio and execution tools, reducing analyst workflow steps from 9 to 4 and cutting average time to generate client reports by 2 minutes.

• Engineered resilient APIs with Java Spring Boot and Node.js, adding regional routing and circuit breakers to preserve data integrity across 3 continents and ensure uninterrupted data delivery during peak loads.

• Reworked legacy valuation modules in C++ and C#, refactoring compute-heavy routines to reduce memory footprint by 700 MB and bringing nightly valuation failures down to single-digit occurrences per month.

• Automated operational runbooks with Python for log analysis, environment validation, and anomaly detection, reducing mean-time-to-detect incidents by 45 minutes and improving on-call transitions.

• Optimized data storage in PostgreSQL and MongoDB through partitioning and read replicas, increasing sustained read/write throughput by 10× during settlement batches and stabilizing processing windows.

• Containerized services with Docker and orchestrated deployments on Kubernetes, implementing health checks and automated failover that achieved <1-minute recovery targets and supported multiple daily releases.

• Strengthened CI/CD and cloud infrastructure using GitLab, Jenkins, Terraform, and AWS by adding integration-test gates and artifact signing so deployments across development, staging, and production completed reliably within single-digit minutes.

• Formed real-time data and monitoring pipelines using Apache Kafka for ingestion, Apache Flink for stream processing, Prometheus for metrics, and Grafana for dashboards, enabling stable processing of millions of events per day and accelerating debugging during trading spikes.