Charishma Agraharam

About Charishma Agraharam

I am a graduate student pursuing a Master of Science in Information Technology and Management at The University of Texas at Dallas. I have a strong foundation in programming and analytics, with proficiency in Python, SQL, R, and Tableau. My coursework includes Cloud Computing Fundamentals, Big Data, System Analysis and Project Management, Database Foundations, and Object-Oriented Programming with Python, equipping me with technical expertise to solve real-world challenges.In my professional experience, I have successfully migrated legacy databases to cloud platforms, resulting in a 35% improvement in access speeds and scalability. With certifications like AWS Solutions Architect Associate and Salesforce Administrator, I am well-prepared to work with modern technologies and deliver impactful results. I aim to grow and excel in dynamic environments while making meaningful contributions.

Experience

1. Software Development Engineer

   Goldman Sachs

   Aug 2024 — Present · US

   Reviewed the existing post-trade enrichment system to understand where delays and rule-handling issues were occurring, and shared improvement recommendations that helped guide the team’s modernization approach. • Converted core enrichment logic into Python microservices using FastAPI, making the system easier to update and allowing us to deploy changes independently without risking stability in other trade flows. • Set up a real-time event ingestion layer on Apache Kafka, enabling the platform to process around 15K+ trade events per second and significantly reducing the lag we saw in the older batch-driven workflow. • Built Spark Structured Streaming jobs to validate, map, and enrich trade attributes, which helped improve data consistency and lowered downstream reconciliation issues by about 18%. • Introduced Open Policy Agent (OPA) to manage entitlement and compliance rules in one place, reducing the number of conflicting rule configurations across different trade flows by roughly half. • Improved database performance in PostgreSQL and MongoDB by restructuring tables, indexing frequently used fields, and optimizing heavy read/write paths, resulting in ~20% faster queries during peak trading hours. • Added Redis caching for high-frequency enrichment lookups, which helped reduce database load and brought API response times down from roughly 280 ms to around 180 ms. • Created a React + TypeScript dashboard that allowed Operations teams to track trade lineage and review exceptions in real time, which cut investigation time by 35–40% and reduced manual follow-ups. • Containerized the new services with Docker and deployed them on Kubernetes with autoscaling and health checks, improving system stability and helping the platform maintain 99.9% uptime during market volatility.

Education

• The University of Texas at Dallas

  Master's degree

  2023 — 2025

• Sri Venkateswara College of Engineering, Tirupati

  Bachelor of Technology - BTech

  2018 — 2022