In this role, I contributed to the Vision Link Productivity (VLP) Project where I primarily worked on maintaining and enhancing the microservices developed in Python and running as Azure Function apps. These microservices played a crucial role in the VLP project as they generated valuable insights using data received from Caterpillar machines generated through sensors attached to the machines. Converted algorithms defined by the data science team into scalable and maintainable codeReduced processing time of huge data by 80% using the Chunking mechanism Optimised the code to reduce memory consumption in Pandas processing by 50%Implemented TVP (Table-valued parameters) in SQL to pass multiple values to a query or stored procedure and use them to filter records. Thus reducing the number of hits to the database.Followed Test-Driven Development via Pytest for reliable, high-quality code

TradeGen Application55-IP Tradegen application is a Django-based application used by the trade execution teams allowing for ongoing portfolio management and monitoring of the accounts submitted through the advisor portal in a scalable manner.Providing the user with different parameters allowing them to identify which accounts need to be rebalanced.The user can select the relevant accounts and send them to the nextgen optimizer to determine the trades.The application then allows the user to review the resulting trades to check the account is brought in line with the various parameters.To complete the operations workflow, the user can seamlessly stage the orders of the desired accounts to the order management system.Key AchievementsCollaborated with team to add new features and enhancements to Tradegen applicationSolved critical bugs and provided technical support.Developed API endpoints to generate reports by processing data using PandasReduced response time for users by implementing optimized algorithms and efficient coding practicesImplemented message queues and worker processes using RabbitMq, resulting in streamlined communication and faster processingCreated python scripts to automate report comparison and perform analysisFollowed the Test Driven Development (TDD) practice by incrementally writing tests using Pytest framework for new and existing features.

LiveChat console is an application built using Angular and Flask Framework it allows real-time conversation between the User and an agent connected through various channels such as Whatsapp, Facebook, and web bots using socketioKey AchievementsDeveloped an micro-service called Assignment service that facilitated efficient allocation of user requests to agents based on a variety of factors including language ,location,contact details etcIntegrated the Assignment service with the Livechat application helping in assigning users to agents Designed and implemented the flow of assigning users to their selected teamsDeveloped and implemented a queuing system for users and assigned them to agents based on their concurrency and availabilitySolved bugs and added new features to the application such as concurrency for agents, Single Sign on using Auth0, Manager analytics, Lazy loading of chats to improve performanceFixed major issues which impacted daily operations in minimal time to ensure availabilty of the applicationDesigned and implemented Single sign-on login for the Livechat console using Auth0Took complete ownership of the product, overseeing its development, testing, and deliveryServed as a Technical Expert in designing, developing, and coding new features and enhancementsData Management PlatformData Management Platform (DMP) is a web-based flask application which allows to configure chatbots and Livechat consoleKey AchievementsDeveloped API endpoints for creating, deleting and updating agents and teamsCreated API endpoints for configuring the Livechat interface settings such as business hours, Customer info etc.Created API endpoints for configuring custom settings for each team such as queuing messages

Index System Control Terminal is a web-based application built using Python 3.6 and the Django framework. This control system automated and also reduced the overall time taken by authenticated business users to trigger corporate actions and daily activities performed in a stock exchange. Index System Control Terminal interacted with different servers through SSH to run scripts on the same. Scripts were triggered using the interface provided to the business user. The application fetched data from the database to generate reports and files used for analysis.I learned Python language and Django Framework from scratch to develop this web-based application.Designed and Created the User interface for the multi-page application using HTML, Javascript and jqueryDeveloped APIs to generate reports in the format required by the business users and transfer them to servers through SFTPCreated a login system using the Framework's inbuilt featuresDeployed the application using Apache server and mod_wsgi with the required security such as SSL