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.
