Open source software development and testing for the Mantid project -
Mantid is a scientific software framework used for the data reduction, visualization and analysis of Neutron and Muon scattering data,
at major scientific facilities like ISIS,
ORNL, and ILL.
Designing, developing, maintaining, and improving DevOps workflows of the project’s CI/CD pipelines.
Developing and implementing Deep learning models to support advanced data analysis and automation for BraggPeak detection.
Tech stack includes C++20, Python3, cmake, Conda, Qt5, Django, Jupyter, Docker, Docker Compose, Ansible, PyTorch, scikit-learn, and use scientific software libraries such as numpy, matplotlib, boost etc.
Architected the MCCP (Millennium Central Counterparty) product and for London Clearing House (LCH) EquityClear, delivering clean, extensible, and maintainable system designs.
Associate Technical Lead - 2020-04 to 2022-04
Led database cutover from Oracle to Postgres for Millennium Central Counterparty (MCCP) and Millennium Risk products, sustaining 2000 trades per second rate
Migrated on-prem Bamboo CI/CD pipelines into AWS cloud for Valgrind, ASAN, gcov, and Smoke testing for MCCP product using Python, Perl, Bash, Bamboo, Jenkins, Terraform, and Ansible
Coordinated with banking and capital market clients and internal teams to provide smooth sprint deliveries
Developed multiple fault-tolerant, distributed gateway processes for MCCP product for London Clearing House (LCH) EquityClear sustaining 5000
trades per second rate: SWIFT ISO15022, DEX, AMC, File, FIXML5.0, and AMC (proprietary) gateways
using C++ 11.
Senior Software Engineer - 2017-07 to 2018-04
Performed comprehensive software development and testing, with BDD with JBehave, unit testing with Google Test/Google Mock, end-to-end testing, and integration within CI/CD pipelines using Agile Scrum practices.
Software Engineer - 2015-05 to 2017-07
Designed and developed high-performance gateways for MCCP product supporting FIXML 4.2, FIXML 4.4, and MMTP protocols using C++11.
Implemented unit tests using Google Test and Google Mock (gtest/gmock) to ensure reliability and correctness.
Recent posts
Python Generators: The Secret to Efficient Iteration
What are Decorators in Python and how do they work?