Researcher • Data Engineer • Developer
New York, NY
AI. Data. Innovation. — Unlocking the Future, One Insight at a Time.
Senior engineer with 9+ years building data-intensive applications across finance, media, and enterprise. Currently pursuing a PhD in Computer Science at Pace University, researching AI and large-scale data systems.
I hold a Master's in Information Systems from Pace University and have worked at companies including Netflix, NASDAQ, Fama Technologies, Principal Financial Group, and Wirb Copernicus Groups — designing modular APIs, automating pipelines, and optimizing data warehouses at scale.
I'm a firm believer that data is the most reliable source of predicting risk and driving innovation. If the technology is available, we need to take advantage of it to elevate the quality of life for people all over the world.
Building end-to-end data pipelines with Python, FastAPI, Snowflake, DBT, Spark, and Airflow. Optimizing data warehouses, automating ETL at TB scale, and designing real-time analytics platforms across AWS, Azure, and GCP.
Developing FCRA-compliant platforms, containerized microservices with Docker & Kubernetes, and full-stack applications using Django, React, React Native, and Node.js — from investment tracking systems to rental platforms.
Author of 16 peer-reviewed research papers across AI, computer vision, urban planning, risk management, healthcare, cybersecurity, and more. Working with TensorFlow, PyTorch, LangChain, and Hugging Face. Holder of 2 granted UK patents.
Developing social media screening platforms that use AI and data analytics to identify potential risks in schools — making educational environments safer for the most vulnerable through proactive, technology-driven solutions.
Starting at Accenture in Bangalore managing enterprise datasets on Azure, I moved to Netflix in Los Gatos where I optimized AWS Kinesis for real-time traffic routing and developed Hadoop MapReduce ETL pipelines processing terabytes of data — reducing pipeline processing time by 40%.
At NASDAQ in New York, I built investment tracking applications and stood up Kubernetes clusters for AI/ML workloads. Then at Fama Technologies, I developed a background check platform adhering to FCRA regulations, containerized with Docker and orchestrated via Kubernetes on AWS EKS.
Most recently at Principal Financial Group and Wirb Copernicus Groups, I've designed modular FastAPI services, automated PDF generation pipelines, deployed DBT on Snowflake, and optimized warehouse queries and costs — all while pursuing my PhD and publishing research in peer-reviewed journals.
Built a full-stack rental platform from scratch in two weeks using Python FastAPI and React Native with PostgreSQL.
An AI-driven chatbot focusing on H1B Visas to provide real-time immigration law information, built with Python, LangChain, OpenAI, and React.
I'm always open to collaborations, research opportunities, or a conversation about how technology can solve real-world problems. Feel free to explore the room and click on other objects to learn more about my work, publications, and experience.
Education, professional experience, and technical expertise.
Pace University, New York, NY
Researching AI and large-scale data systems. Author of 16 peer-reviewed papers spanning AI, computer vision, urban planning, risk management, healthcare, cybersecurity, and data engineering. Holder of 2 granted UK patents.
Pace University, New York, NY
Advanced coursework in machine learning, distributed systems, and data analytics. Foundation for building scalable data solutions across enterprise environments.
Wirb Copernicus Groups • Remote
Designed modular APIs using FastAPI, automated PDF generation pipelines, and optimized Snowflake data warehouse queries and costs.
Principal Financial Group • Remote
Built end-to-end data pipelines from 3rd-party apps to Snowflake and S3. Deployed and maintained DBT models on Snowflake. Implemented data quality checks and monitoring.
Fama Technologies • Remote
Developed a background check platform adhering to FCRA regulations. Containerized services with Docker and orchestrated deployments via Kubernetes on AWS EKS.
NASDAQ • New York, NY
Developed a finance application tracking investments and invoicing. Implemented Kubernetes clusters for AI/ML applications. Integrated real-time market data feeds.
Netflix • Los Gatos, CA
Optimized AWS Kinesis streams for real-time traffic routing. Developed Hadoop MapReduce ETL pipelines at TB scale. Reduced pipeline processing time by 40%.
Accenture • Bangalore, India
Managed large enterprise datasets using Azure SQL Database. Built CI/CD pipelines with Azure DevOps. Automated testing and deployment workflows.
Serving as a judge, reviewer, and panelist across academic and industry events.
What colleagues, mentors, and collaborators have to say.
Professional organizations and communities I'm part of.