Designed, developed, and maintained full-stack applications (Django, Flask, NextJS) to enable core trading system performance and management, including centralized interfaces for trading app configuration to simplify daily processes, back-end services that enforced compliance-critical ISO routing logic to enable the firm to engage in sweep ordering, and Kafka ETL pipelines to replace legacy services and provide trade data often minutes faster, preventing thousands in potential PnL daily.

Managed deployment lifecycle of core trading application releases by building CI/CD pipelines (Bamboo, Ansible, Helm), performing UAT, and maintaining/diagnosing on-prem and cloud-hosted Kubernetes infrastructure including technologies like Hazelcast, Kafka, Spark, Airflow, and proprietary Java/C++ apps

Implemented distributed metric monitoring solutions leveraging Prometheus, Alertmanager, Thanos, Grafana, mtail, and React, utilizing cross-datacenter metric federation to reduce daily logging footprint (in many cases from TBs to MBs) while increasing critical system uptime substantially across dozens of core systems and thousands of application instances

Collaborated with various stakeholder teams (Risk, Compliance, Trading, Business Dev, Quant Research, Sales) to define requirements for core application feature requests

Served as primary on-call support for trading floor, including emergency triage of trading application/system failures, exchange connectivity outages, and market data or ordering session interruptions

Conducted thorough post-incident documentation and ticketing, including sub-microsecond latency sensitive signal processing analysis, to determine root cause of performance issues and bugged app behavior

Interviewed, trained, and mentored new team members on global system architecture and deployments, and also participated in internal project-planning and priority assessment

Contracted and performed for gigs of various sizes and functions. Proficient in jazz piano, jazz and rock guitar/bass; next project is tenor saxophone

Hackathon: Graph Implementation using Asynchronous Syntax Trees - Best Tech Hack

Productionized market predicting alpha models utilizing Pandas and MongoDB

Containerized and refactored research backtester code using Docker

Expanded unit and regression testing suite to increase codebase coverage

Collaborated with market research teams to translate legacy SAS code to Python