Software Engineer at BG Products, USA

Designed and implemented data processing pipelines to analyze large-scale system performance datasets using Python and SQL, enabling near real-time insights and improving evaluation efficiency by 35%. Developed Python-based tools and microservices to compute, aggregate, and visualize key performance metrics across distributed applications to enhance observability and decision-making. Built scalable backend services using .NET Core and C# with ASP.NET Core APIs, processing 2M+ monthly transactions while reducing latency by 30%. Established data validation and quality control frameworks for high-volume datasets. Containerized applications using Docker and implemented CI/CD pipelines via Azure DevOps, improving deployment reliability and reducing production failures by 28%. Collaborated cross-functionally to define performance KPIs, monitoring strategies, and readiness benchmarks.

Software Engineer at State Street, USA

Engineered data-driven performance analytics pipelines using Python, SQL Server, and Kafka for real-time processing and sub-2-second insights in financial systems. Developed metric computation frameworks and dashboards to evaluate throughput, latency, and reliability, improving operational visibility by 40%. Built full-stack applications using React, TypeScript, and .NET Core, reducing onboarding time by 30% while integrating performance tracking. Optimized large-scale datasets via SQL tuning and indexing to accelerate analytics workloads by 45%. Implemented data quality validation checks and anomaly detection logic to ensure mission-critical data pipeline integrity. Led Agile development with CI/CD using Azure DevOps and GitHub Actions to improve release cycles and delivery consistency.