Kiran Matthews

Kiran Matthews

Data Engineer/Analyst @ IRIS Software

About Kiran Matthews

Kiran Matthews is a Data Engineer/Analyst with experience in both on-premise and cloud-based data solutions. He has worked at Mastek and currently at Iris Software Inc., where he has developed frameworks and managed ETL pipelines to enhance data efficiency.

Work at IRIS Software

Kiran Matthews has been employed at IRIS Software Inc. as a Data Engineer/Analyst since 2022. In this role, Kiran has orchestrated and implemented various data engineering components for both on-premise and cloud-based solutions. This work has enhanced efficiency and agility for thousands of developers. Kiran has also managed the deployment of a cloud-based ETL pipeline utilizing CI/CD toolsets, which resulted in a 50% reduction in deployment time and improved scalability.

Previous Experience at Mastek

Prior to joining IRIS Software, Kiran Matthews worked as a Data Analyst at Mastek for a period of six months in 2018. This role was based in Mumbai, Maharashtra, India. During this time, Kiran gained valuable experience in data analysis, contributing to the organization's data-driven decision-making processes.

Education and Expertise

Kiran Matthews holds a Bachelor of Technology (BTech) degree in Information Technology from SVKM's Narsee Monjee Institute of Management Studies (NMIMS), where studies were completed from 2015 to 2019. Kiran furthered education by obtaining a Master of Science (MS) in Business Analytics from the Rochester Institute of Technology, completing this program from 2020 to 2022. This educational background provides a strong foundation in data engineering and analytics.

Data Engineering Contributions

In the current role at IRIS Software, Kiran Matthews developed a configurable framework to archive rarely used data from the client's enterprise data lake to the IBM S3 cloud. This initiative led to significant cost savings for the organization. Kiran's contributions in data engineering focus on enhancing data management and operational efficiency.

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