Rupesh Patidar
About Rupesh Patidar
Rupesh Patidar is a Senior DevOps Engineer with expertise in automation using Terraform and significant experience in AWS and Azure cloud services. He has worked for various companies in Bengaluru, India, including QBurst, Cimpress India, Happiest Minds Technologies, and OnMobile Global Limited.
Work at Cimpress
Rupesh Patidar has been employed at Cimpress India as a Senior DevOps Engineer since 2021. In this role, he focuses on implementing and managing DevOps practices within the organization. His responsibilities include automating processes and enhancing system efficiencies. His tenure at Cimpress has contributed to his professional growth and expertise in the field.
Previous Experience in DevOps
Prior to joining Cimpress, Rupesh Patidar worked at QBurst as a Senior DevOps Engineer from 2019 to 2021, where he gained valuable experience in the DevOps domain. He also held a position at Happiest Minds Technologies for six months in 2019. His career began at OnMobile Global Limited, where he served as a DevOps Engineer from 2017 to 2019. This cumulative experience has equipped him with a strong foundation in DevOps practices.
Education and Expertise
Rupesh Patidar holds a Bachelor of Engineering degree in Computer Science and Engineering from Jawaharlal Institute of Technology, Khargone. He furthered his education by completing a Post Graduate Diploma in Information Technology Infrastructure Systems and Security (PG-DITISS) at C-DAC ECITY, Bengaluru, where he studied cybersecurity and network security. His educational background supports his expertise in cloud services, particularly AWS and Azure.
Technical Skills and Specializations
Rupesh Patidar possesses around 5.8 years of experience in cloud services, specifically AWS and Azure. He is skilled in automation tasks using the Terraform tool and has a strong command of networking, Linux, CI/CD processes, and Docker container environments. His technical skills enable him to effectively contribute to DevOps initiatives and improve operational efficiencies.