Built Fintech-enabled products that allowed cross-border payments.

Built and maintained GraphQL API’s which powered all the applications that served customers interested in various public services across various sectors in the USA.Designed and built ETL Pipelines which was used to scrape public data from the web, transform, and save the data in a Graph Database (Neo4J) coupled with Elastic search and MongoDB.Implemented job queues that served in the ETL Pipelines.Migrated REST APIs to a GraphQL which was implemented using the GRANDStack.Setup Message Queues using RabbitMQ, which was used to do background processing of databeing passed across all platforms of the company which made all systems decoupled in nature.Setup and implemented Redis for caching data used to make response rate faster and reducedthe number of trips to the database

Migrated some of the company’s client legacy software to a microservice architecture using NodeJS as the runtime environment, Express.Js, MongoDB, RabbitMQ. This led to a 50% increase in the number of requests the programs handled, reduced the latency by 30%, and also made it easier to maintain in the long run.Migrated the backend service of the company’s flagship product to a microservice architecture. I used NodeJs, Express, MongoDB to achieve this. This reduced the latency usually experienced when using the mobile application by 60% as the users gave good feedback on the increased speed experienced when using the application.Built a farm project application which was intended to be used on a large scale farm to manage all activities. I achieved this using ReactJs, MongoDB, Redis, and NodeJS. This led to a drastic reduction in the manual process and made the farming experience more automated, which in turn reduced the number of phone calls made across the farm by 70%.I was also involved in making some architectural decisions that were used to develop the applications of some clients. The company went on to adopt this architecture for its simplicity and structure (Clean Code Architecture) as they found that the codebase could be maintained without much hassle. This move sped our development by 40% as we could run iterations faster without breaking things already in place. It also helped us to build microservice applications faster and cleaner.Performed regular analysis and debugging of applications to remove any bottleneck thereby making sure the application runs smoothlyIncreased the quality of codes being shipped by 50% by introducing the use of Codacy and test coverage tools to the development team.