Achieved a 40% reduction in Questa HDL parallel simulation execution times through the implementation of smart profiling-driven rebalancing of execution patterns, demonstrating proficiency in C, MPI, and GDB.

Automated the merging of log files from parallel simulations, creating a unified view for streamlined analysis and debugging.

Accelerated historical financial simulations and risk reporting by 80% in C++ by optimizing state file memory load time. Utilized multithreaded decompression with the lz4 library and parallel deserialization using Boost thread pool.

Strengthened security of 3 major trading systems by integrating TLS protocol into all C++/Python socket communications. Leveraged the OpenSSL library to enable robust authentication and encryption mechanisms.

Implemented a price update module for ETFs, leveraging Apache Kafka to receive real-time quotes and efficiently handle up to 10K messages/second. Ensured precise and timely pricing for effective trading decisions.

Developed 50+ optimized quant metrics in C++/Python for security modeling, portfolio management, and risk analysis.

Actively took the lead in interviewing candidates for internships and full-time Software Engineering roles, contributing to the growth of our team.

Initiated and participated in an outreach initiative called Ascend Educare, where I taught Object-Oriented Programming (OOPs) and C++ concepts to undergraduate students, helping them enhance their skills and knowledge in the field.

Accelerated access to financial time-series data (over 25 TB) by an impressive 2000% compared to Data Warehouse queries. This achievement was made possible by developing a high-performance vectorized cache library in Python, leveraging NumPy and HDF5 file format.

Facilitated historical data access for 12+ strategy teams by creating GraphQL APIs over Django. These APIs were seamlessly integrated with the cache library, ensuring cross-language compatibility, flexible queries, and efficient data retrieval.

Reduced cache maintenance and update requests by a substantial 80% by devising a highly flexible mechanism in Python. This allowed for seamless modification to the underlying cache configuration.

Developed interactive visualizations for historical stock and portfolio data analysis, leveraging React, D3.js, and Django backend.

Improved developer productivity by significantly reducing the build time of the 100K+ lines of C++ codebase by 60%. This achievement was accomplished through the implementation of CMake, ccache, migration to C++14 from C++98, and upgrading the GCC version.