Cloud Engineer

Location Address: Downtown Toronto - Hybrid model (2-3 days a week in office) Contract Duration: 3 months – possible extension for 6 months till end of the project Possibility of extension & conversion to FTE – Depending on performance Schedule Hours: 9am-5pm Monday-Friday (No overtime) Typical Day in Role: • Manage GCP Cloud Infrastructure: Design, build, and implement solutions around standard public cloud services like, Google Cloud Storage, Bigquery, Dataproc, Vertex AI Notebooks, Cloud Run and Cloud Functions among others, Using Terraform Modules. • Release Control Management: Maintain and enhance the Release Control Management pipeline using Terraform, Cloud build and GitHub Actions and Bitbucket/GitHub repositories. • Client Pipeline Management: Implement CI/CD process by designing industry standard Cloud Build for deploying Infrastructure and analytics workloads using Terraform, Docker, Cloud build, GitHub Actions, Artifact registry and other build / deployment activities • Credential Security: Setup Hashicorp Vault and Secret Manager for secret management. Integrate security solutions with client interfaces • Client User Acceptance Testing: Lead clients in user acceptance testing for component and base image upgrades, ensuring smooth transitions and minimal disruptions. • Advanced Monitoring and Troubleshooting: Troubleshoot and resolve performance issues to ensure optimal system performance. • Vendor and Technical Support Interaction: Regularly meet with product vendors and technical support to fine-tune and troubleshoot software components, ensuring the highest level of system performance and reliability. • Client Support: Assist tenants with troubleshooting their issues related to GCP and its services • Mentorship: Mentor junior engineers in best practices for building, deploying, testing, and supporting services, fostering a culture of continuous learning and improvement. •Provision, configure, and manage Hadoop clusters within the Dataproc environment. •Optimize Dataproc cluster configurations for performance, cost-efficiency, and stability. Candidate Requirements/Must Have Skills: • 5 years of experience in managing a public cloud platform for an enterprise on GCP, Azure or AWS with technical expertise in Foundational and Data services • 3 years of experience in using Infrastructure as Code tooling Like Terraform to manage large-scale infrastructure platforms with strong knowledge of best practices for access control and least-privilege policy • 5 years of experience in DevOps, building CI/CD pipelines using GitHub, Artifactory etc. to reduce cycle times and ensure quality. • 10 years of IT experience in managing and developing applications or platforms ensuring scalability, reliability, and security. • 2 years of experience in public cloud-managed services for Data and Analytics for data warehousing, data lakes, ETL services, machine learning or data governance and security • 5 years of experience in Languages like Python, Go, or Java & scripting skills in (shell scripting, Python, Perl, Ansible) to automate tasks, create scripts, and develop infrastructure as code. Nice-To-Have Skills: •Experience in managing and administering Hadoop clusters (e.g. Cloudera, Dataproc, Hortonworks). strong understanding of Hadoop ecosystem and its core components • Certification in GCP (GCP Cloud Associate) is desirable. • Experience with Docker/Container - including setting up and managing Docker registries as well as creating Docker files to create custom images. Should know about overlay networking needed for inter-container communications from different nodes as well as external servers/infrastructure • Experience in setting up Kubernetes or similar platforms on-premises/cloud (On-prem Rancher experience is a plus) Best VS. Average Candidate: The best candidate is someone hands-on experience with Terraform, and implamanttion using AWS, Azure, or GCP preferable. Someone who is thorough and knowledgeable, a self-starter, takes pride in their work, and is a hard worker. they will search for Candidate Review & Selection 2 Rounds of interviews 1st round with the Technical team – Video call Ms teams 1 hour – Talk about work experience and get to know (no technical assessments or business case required) 2nd round – Hiring manager and Director – Video call Ms teams 30 mins- Talk about experience and behavioral questions.