Nazim is a full-stack developer with more than 17 years of C# experience. He has developed highly scalable, resilient, and robust microservices. In addition to proven back-end experience, he developed single-page applications (SPA) using the Angular framework on the front-end. He has worked on Azure Cloud-based projects, where he's used Azure Durable Functions, Azure Service Bus, Azure Storage, and Azure Cosmos DB.
Migrated the application implemented on Azure Data Factory to Azure Durable Functions which is a Serverless architecture.
Designed the application's central logging mechanism and fed it into Azure Application Insight.
Prepared build pipelines to create artifacts and to publish Nuget packages for the common libraries using Azure DevOps.
Integrated due diligence workflow with Orbis API to get company information like sector, rating, etc.
Managed to run Azure Functions as a Docker Container on the VM, because of the reason there was a data restriction and Azure Functions were not supported by Microsoft in that region.
Integrated Azure Functions with HiqhQ Collaborate Tool's REST API using OAuth2.0 authentication.
Prepared high level and technical design documents for the integrations of seven different HSBC global applications.
Implemented integrations of seven different HSBC global applications between Turkey, Hong Kong, United Kingdom, and the USA using IBM MQ. Integrations had Global Payments transactions of SWIFT, EFT, Tax, Custom and Invoice payments.
Designed a central database and request/response logging system on MS SQL 2014 for the integrations.
Redesigned and implemented a Java-based in-house legacy risk evaluation system (ScoreCard) using .Net framework that processed 700,000 credit applications received via SMS.
Implemented a credit decision application using .Net framework from scratch.
Managed and developed an infrastructure for the web performance load test of the entire integrated core banking system with 30 virtual servers and more than 10,000 virtual users.
Contributed to a machine learning project for a startup company. Developed application to do text clustering, text extraction, title, and content identification of data that was coming from image OCR API using Python.
Developed REST API using Flask to liaise with React front-end developers.
Implemented utilities to test processes and wrote results back to the source image file. The result was drawn as a box with correct coordinates onto the image file like title, identified content, location, or document identity number.