Architected and delivered mission-critical backend APIs and services for a large-scale Inventory Management platform, supporting 36k clinical trials and 11 million patients globally.

• Owned the end-to-end development of a real-time cold chain monitoring system, ensuring system reliability and strict compliance with FDA & HIPAA regulations in a high-stakes environment.

• Led the architecture and delivery of a highly scalable, real-time data processing pipeline using Kafka, Debezium, AWS Glue and PyArrow, reducing data latency by over 50% to power visual analytics.

• Built flexible Live RTSM Cohort Management functionalities, facilitating dynamic changes for sequential and parallel patient enrollment throughout clinical study progression.

• Help engineers identify opportunities for developing a strong technical

skillset while having impact on the team and Medidata. Established a culture of engineering excellence by leading architecture reviews and providing comprehensive technical guidance to a globally distributed team.

ETF Analytics Team

• Spearheaded the technical integration of the multi-million dollar ETF.com acquisition, ensuring seamless

operational continuity and data migration into FactSet's platform.

• Achieved annual savings of $100K by successfully transitioning from TALEND ETL to custom Python-based

data feeds.

• Provided critical technical leadership for the FactSet ETF Analytics platform, overseeing complex data collection,

integration, and computation processes.

• Managed and optimized end-to-end data ingestion, analytics, and customer feed delivery for the ETF Team.

• Led and mentored a high-performing global team of developers across US, India, France, and the Philippines,

fostering collaboration and project success.

DataFeed Engineering

• Engineered and optimized data transformation pipelines using AWS Glue and PyArrow, enhancing overall data

processing efficiency.

• Developed robust data ingestion solutions for scraping, consolidating, validating, and cleansing data from a vast

range of sources, including applications, databases, and APIs.

• Accelerated data feed performance by more than 50% through strategic implementation of Apache Spark for

large-scale data processing.

Content Collection Services Engineering providing data collection solutions for FactSet Ownership database

• Modernized critical legacy Visual FoxPro applications by rewriting them into C# desktop applications utilizing

WPF, MVVM Light, Log4Net, and Entity Framework. which improved data collection metrics by over 50%.

• Improved the Daily/Full Re-positioning process, reducing execution time by over 85% (from 15 hours to 2

hours), significantly improving operational efficiency.

• Collaborated cross-functionally with diverse stakeholders to identify and implement workflow and application

enhancements, optimizing analyst performance by over 30%.

Developed and maintained features in System Pulse, Epic's web based system monitoring tool designed for IT staff and system administrators’ at large health care providers. My responsibilities include:

• Gathering requirements.

• Performing technical analysis.

• Designing, developing and testing software modules.

Project 1: Custom Graph Control

The main objective of this project was to create a custom chart control to replace existing System Pulse graphing capabilities and to reduce long-term development, testing and maintenance time.

• Prepared a design document containing scope of changes, critical issue analysis and initial timelines to highlight how the use of this new control will enhance System Pulse graphing capabilities.

• This web control is used to graph Cache Growth Monitor data, which helps health care providers to project the size of file systems and datasets for future time frames based on historical data and rate of growth.

Project 2: System Pulse Diagnostic Features.

The new System Pulse Diagnostics features were created to help troubleshoot situations where the data is missing from System Pulse and to make the application more robust.

• Interacted with different internal teams to gather the requirements and prepared the design document.

• Made extensive infrastructural changes at every level (Server code, Node Agent, Web App, Database) and added a user interface to display the information in a meaningful way.