Engineered Python/Django/FastAPI-based microservices for risk modeling, scenario simulation, and portfolio optimization, integrating REST APIs with client trading systems. Developed ReactJS + Typescript dashboards with Plotly/D3.js to visualize market risk, liquidity metrics, and stress test results, enabling real-time decision-making for executives. Built scalable ETL pipelines using Python, Pandas, NumPy, PySpark, and SQLAlchemy to ingest and normalize multi- source datasets from Bloomberg, Reuters, and proprietary feeds. Optimized database performance with PostgreSQL and MongoDB, achieving 40% faster query responses. Partnered with data science teams to operationalize machine learning models and integrate TensorFlow, PyTorch, and LLMs for predictive risk scoring, fraud detection, and natural language–driven insights. Containerized workloads with Docker/Kubernetes and deployed to AWS (ECS, Lambda, RDS, S3). Automated provisioning with Terraform and Ansible, ensuring consistent, cloud-native deployments. Reduced computational overhead via asynchronous task queues (Celery, RabbitMQ) and parallel processing. Enhanced security with QAuth2/JWT authentication and API Gateway integrations, aligned with SOX and Basel III compliance. Automated regulatory reporting workflows with Python, reducing manual prep time by 50% for audit teams. Implemented CI/CD pipelines (Jenkins, GitHub Actions) and real-time monitoring with ELK Stack and Grafana. Collaborated in Agile sprints with consultants, analysts, and developers, ensuring alignment with business goal

Worked on microservices to collect and process telematics data from IoT-enabled engines and power systems, enabling real-time insights for operators and enterprises. I built ReactJS dashboards and real-time visualizations (D3.js, Plotly), to track fleet performance, fuel consumption, emissions data, and predictive maintenance alerts. To ensure seamless connectivity, I developed REST APIs that integrated on-vehicle sensors, mobile applications, and enterprise ERP systems. For large-scale data ingestion, I designed pipelines with Python, Kafka, Pandas, and SQLAlchemy, capable of processing millions of IoT messages daily, while optimizing PostgreSQL and Oracle queries through partitioning and indexing, reducing report generation times by 40%. I implemented asynchronous task handling with Celery and RabbitMQ, enabling real-time alerting and event processing at scale. Compliance workflows were automated with Python scripts, ensuring adherence to EPA and ISO standards while reducing manual reporting efforts by 50%. I deployed scalable applications on AWS (ECS, Lambda, RDS, S3) and automated infrastructure provisioning with Terraform, strengthening system reliability and efficiency. Security was reinforced using OAuth2/JWT authentication and RBAC models for role-specific fleet data access. To further boost performance, I introduced Redis-based caching layers, delivering sub-second response times for global users. Working closely with data science teams, I integrated AI-driven predictive diagnostics models, preventing costly engine failures and improving asset reliability. I streamlined DevOps workflows by implementing CI/CD pipelines (Jenkins, GitHub Actions), enabling faster rollouts of fleet management applications. I also conducted load and stress testing with Locust and JMeter to validate system reliability under 10K+ concurrent vehicle connections. Ultimately, these solutions reduced unplanned downtime by 20%, improved fleet efficiency, and optimized fuel usage, delivering measurable business value to commercial clients.

Delivered cloud-native data management solutions by orchestrating Python and Node.js microservices on AWS using Docker and Kubernetes, ensuring 99.9% system uptime. I transformed high-volume datasets into actionable insights by designing Python + Pandas data pipelines, accelerating data availability for clients by 35%. To enhance user experience, I built ReactJS dashboards with D3.js/Plotly, giving stakeholders real-time visibility into system health and key performance indicators. I spearheaded the migration from on-premise to containerized cloud platforms, reducing infrastructure costs by nearly 25% while improving deployment agility. To strengthen security and compliance for financial and healthcare sector clients, I implemented RBAC security models and OAuth2 authentication. I also automated continuous delivery through Jenkins pipelines and Terraform Infrastructure as Code (IaC), cutting release cycles from weeks to days. Performance was further optimized by enhancing data-heavy APIs with Redis caching and Celery task queues, enabling near real-time processing of critical business data. Additionally, I championed peer code reviews and introduced robust testing frameworks (PyTest, unittest), significantly improving code quality, maintainability, and overall team productivity across multiple client projects. Beyond delivery, I mentored junior developers on Python best practices, Git workflows, and agile methodologies, fostering a culture of clean coding and continuous delivery.

I engineered full-stack financial platforms using Python (Django/Flask), React, and SQL, enabling portfolio analytics, trade reconciliation, and client reporting with 40% faster processing. To streamline operations, I built REST APIs and Python/Django and Node.js microservices that automating data ingestion, cleansing, and transformation of multi-source financial feeds, including equities, bonds, and mutual funds. I developed interactive dashboards with React/Angular, providing fund managers and analysts with real-time investment performance insights. To ensure security and scalability, I implemented OAuth2/JWT authentication, leveraged containerization with Docker, and deployed solutions on AWS through Jenkins CI/CD pipelines, I modernized legacy VBA/.NET tools into Python-based services, improving overall reliability and maintainability. Partnering with cross-functional teams in Agile sprints, I aligned technology solutions with financial compliance standards (SEBI, SOX), accelerating release cycles and ensuring regulatory adherence.