CLOUD SPECIALIST

• Develop and provide cloud computing services (platform-as-a-service or infrastructure-as-a-service) suggestions/proposals for SME, Enterprise and various industry verticals.

• Design data solutions aligned to the design principles and security standards of the Google Cloud Platform.

• Design and implement solutions around data warehouse implementation ranging from architecture, ETL processes, multidimensional modelling, data marts implementation.

• Design and optimize data acquisition, data ingestion, data processing using ETL (Extract, Load, Transform) tool and developing dashboards or other visualizations using Google Cloud Platform or other solutions.

• Evaluate the requirements and determine actionable tasks, estimates and provide efforts for business solution build and architecture.

• Responsible for technical documentation on solution implementation.

• Perform operational readiness tasks and ensure production acceptance criteria are met.

• Respond to platform technical issues in a professional and timely manner.

• Work closely with the sales team for cloud-related sales opportunities.

• Support Pre-Sales activities, i.e. proposal, systems design, proof-of-concept, demo, workshop conduct, etc. Requirements:

• Bachelor’s degree in Computer Science, related technical field, or equivalent practical experience.

• 3 – 5 years of experience in Business Analytics, Data Engineering or Data Science.

• Strong logical/analytical troubleshooting.

• Experience in deploying and operating multi/hybrid-cloud platforms, such as Kubernetes, Anthos etc is a plus

• Working closely with multiple teams (Engineering, Security, Operations & Development teams) to maintain, deploy and operate containerized solutions

• Work with computer engineers to integrate software systems • Hold hands on role that consists of administrating Mirantis(Former Docker Enterprise) based Kubernetes cluster, containerizing apps

• Spreading the usage of containers in the company through automation and coaching

• Deploy and configure solutions in the cloud.

• Managing Kubernetes platform

• Automating the provisioning of environments

• Troubleshooting incidents / problems

• Thriving for continuous improvement of the production environment

• Redesigning legacy applications for container implementation

• Assist on DR, BCP exercise and patching cycles