Cloud Native Software Engineer

2 weeks ago

Montreal, Quebec, Canada Groupe SII Full time
About the Role

Groupe SII is seeking a highly skilled Cloud Native Software Engineer to join our team. As an AWS/K8S Engineer, you will be responsible for designing, developing, and maintaining cloud-native architecture solutions for our applications.

Key Responsibilities
  • Product Development: Develop and maintain products that will be used by our Data Science community, ensuring they meet the required standards and are scalable.
  • Cloud Architecture: Design and implement cloud-native architecture solutions for our application needs, particularly with AWS, ensuring they are secure, efficient, and cost-effective.
  • Infrastructure-as-Code: Utilize Terraform and AWS Cloud Formation to provide infrastructure-as-code, ensuring consistency and reproducibility across our environments.
  • Platform Support: Provide support for our platform, ensuring it is stable, secure, and meets the required performance standards.
  • Cloud Infrastructure: Provision and maintain cloud infrastructure that will support training machine learning models, ensuring it is scalable and meets the required standards.
Requirements
  • Technical Expertise: Wide experience with Kubernetes and Docker is a must-have. Industry experience with Amazon Web Services, IAM, VPC, API Gateway, NLB, ALB, EC2, ECS, EKS, Lambda, S3, RDS, DynamoDB, SQS, etc. is also required.
  • Programming Skills: Candidate must have knowledge of Linux systems, experience in Python and Bash scripting, and experience in CI/CD/CT pipelines implementation.
  • Networking and Database Knowledge: Good understanding of networking and related protocols (DNS, TLS, TCP), and knowledge of database technologies.
  • DevOps Toolkit: Familiarity with the DevOps toolkit (Terraform, Ansible, Chef, and other tools) and exposure to messaging pub/sub systems (e.g. AWS SNS, SQS, RedisQ etc.) is required.
  • Data Science and Machine Learning: Exposure to data science IDEs like Rstudio, Jupyter notebook, and SAS studio is a huge plus, as well as understanding of Machine Learning workflow and apps like Kubeflow and Sagemaker studio.

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