5 Cloud Computing jobs in Quebec

Job Description

We are looking for an experienced Cloud DevOps Engineer for our client. This is a permanent position that is remote to start with later relocation to Calgary or Winnipeg . Our client is a global enterprise company with a product that you've likely used.

This position requires the ability to code as well as perform the duties of a DevOps Engineer. Previous experience as a Software Engineer/Developer will be regarded highly.

You Have:

• 4+ years’ experience working as a DevOps Engineer
• 2+ years' experience coding/building applications as a Software Engineer

• Experience with Public API solutions, such as AWS API Gateway, and WAF solutions, such as Incapsula

• Experience with AWS SNS/SQS, RabbitMQ, Kinesis, Kafka or Pusher
• Extensive experience working wit AWS cloud platform
• Great communication skills and the ability to communicate technical concepts with ease

Perks:

• Competitive Salary
• Individual performance bonus
• Health and dental benefits
• 3 weeks’ vacation
• Relocation Package

If this opportunity sounds like something that fits your career path, please apply to this posting; we'd love to talk to you!

Job Description

Salary:

About the Role

We are hiring a Senior Cloud Data Engineer to lead the development of our cloud infrastructure that powers AI/ML product pipelines from data ingestion and orchestration to model deployment and secure application delivery.

This is a deeply hands-on engineering role, responsible for designing, coding, and maintaining scalable, secure, multi-tenant data environments across AWS and Azure. You will play a central role in building infrastructure to support AI/ML use cases such as demand forecasting, predictive analytics, and real-time decision-making.

This is a hands-on, engineering-heavy role ideal for someone who thrives in high-responsibility environments, demonstrates sharp problem-solving skills, and takes initiative to independently deliver robust solutions from end to end.

Key Responsibilities

Cloud Data Engineering & Architecture

• Architect and build scalable, secure, multi-tenant cloud data pipelines in AWS and Azure
• Implement robust ETL/ELT pipelines and APIs to move and access data across Oracle, AWS, and Snowflake including ERP-to-cloud, cloud-to-ERP, and intra-cloud flows
• Leverage AWS services (Glue, Lambda, S3, RDS, EventBridge), AWS Batch, Azure components, and orchestration tools like Airflow and Kedro to build resilient and maintainable pipelines; Enforce modularity and reusability.
• Automate infrastructure provisioning using Terraform / OpenTofu; manage CI/CD pipelines with Jenkins, GitHub Actions, or ArgoCD.

AI/ML Infrastructure & MLOps

• Build infrastructure to support AI/ML workflows (e.g. training, validation, versioning)
• Integrate with experiment tracking tools (e.g. MLflow) and model lifecycle pipelines
• Enable scalable model deployment in secure environments (containerized or cloud-native)
• Support full ML Ops lifecycle: data prep, parameter tuning, model deployment, and monitoring, in close collaboration with AI/ML scientists.

Secure Application Deployment

• Deploy and manage React or Python-based ML applications with secure user access
• Ensure private networking, MFA, RBAC, and encryption best practices in Azure and AWS
• Create CI/CD pipelines (e.g., Jenkins, GitHub Actions) integrated with Docker/Kubernetes

Automation & DevSecOps

• Design end-to-end automation for data movement, transformation, and model execution
• Integrate automated testing, scanning, and rollback strategies into CI/CD pipelines
• Maintain monitoring and logging with Prometheus, CloudWatch, or similar tools

Cross-Platform & Multi-Cloud Strategy

• Build portable components deployable across AWS and Azure
• Support integration of services like AWS Batch, AWS Glue, S3, Lambda, EventBridge, etc

ERP and Retail Context

• Work with ERP-based datasets (Oracle), including complex relational structures
• Understand the unique needs of AI applications in retail and supply chain analytics

Qualifications

Education & Experience

• Masters degree in Data Science, Computer Science, or Software Engineering
• 5+ years of real-world experience in cloud data engineering, infrastructure, and deployment roles
• Prior professional experience with AI/ML pipelines or applications is strongly preferred

Tech Stack & Tools (Must-Have Experience)

• AWS (S3, Lambda, Glue, RDS, IAM, EventBridge), AWS Batch, Azure
• Snowflake, Oracle, SQL
• Python, PySpark, Docker, Kubernetes, Terraform
• Airflow, MLflow (for tracking), Git, CI/CD pipelines

Traits We Value

• Self-driven, independent, and resourceful able to own solutions from idea to production
• High attention to detail and a deep respect for secure, responsible data handling
• Collaborative mindset to work with data scientists, product managers, and architects
• Excellent written and verbal communication

Additional Information

• Remote Work Model: Hybrid; 2days per week in the Montreal office

We thank all applicants for their interest; only those shortlisted will be contacted.

Join us to help build the cloud foundations of our AI-powered future!

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propos du poste

Nous recrutons uneSenior Cloud Data Engineer pour piloter le dveloppement de notre infrastructure cloud, support des pipelines produits IA/ML de lingestion et lorchestration des donnes au dploiement des modles et la livraison scurise des applications.

Ce rle trs oprationnel consiste concevoir, coder et maintenir des environnements de donnes scalables, scuriss et multilocataires sur AWS et Azure. Vous jouerez un rle central dans la cration dinfrastructures pour prendre en charge des cas dusage IA/ML tels que la prvision de la demande, lanalytique prdictive et la prise de dcisions en temps rel.

Ce poste, forte dimension technique et autonome, est idal pour une personne qui spanouit dans des environnements haute responsabilit, fait preuve dun excellent sens du problme et prend linitiative pour livrer de bout en bout des solutions robustes.

Responsabilits cls

Ingnierie & architecture des donnes cloud

• Concevoir et btir des pipelines de donnes cloud scalables, scuriss et multilocataires sur AWS et Azure.
• Implmenter des pipelines ETL/ELT et des API robustes pour dplacer et accder aux donnes entre Oracle, AWS et Snowflake (ERPcloud, cloudERP, intracloud).
• Exploiter les services AWS (Glue, Lambda, S3, RDS, EventBridge), AWS Batch, composants Azure et outils dorchestration (Airflow, Kedro) pour garantir rsilience et maintenabilit, en privilgiant modularit et rutilisabilit.
• Automatiser le provisionnement dinfrastructure avec Terraform/OpenTofu ; grer les pipelines CI/CD via Jenkins, GitHub Actions ou ArgoCD.

Infrastructure IA/ML & MLOps

• Mettre en place linfrastructure pour les workflows IA/ML (entranement, validation, gestion des versions).
• Intgrer des outils de suivi dexprimentation (MLflow) et orchestrer les pipelines de cycle de vie des modles.
• Permettre le dploiement scalable des modles dans des environnements scuriss (conteneurs ou cloud natif).
• Couvrir le cycle MLOps complet : prparation des donnes, ajustement des paramtres, dploiement des modles et surveillance, en collaboration troite avec les data scientists.

Dploiement dapplications scuris

• Dployer et grer des applications ML bases sur React ou Python avec accs utilisateur scuris.
• Mettre en uvre rseau priv, MFA, RBAC et chiffrement selon les meilleures pratiques Azure et AWS.
• Crer des pipelines CI/CD (Jenkins, GitHub Actions) intgrs avec Docker/Kubernetes.

Automatisation & DevSecOps

• Concevoir lautomatisation de bout en bout pour le dplacement, la transformation des donnes et lexcution des modles.
• Intgrer tests automatiss, scans de scurit et stratgies de rollback dans les pipelines CI/CD.
• Maintenir la surveillance et la journalisation avec Prometheus, CloudWatch ou outils similaires.

Stratgie multicloud & crossplatform

• Dvelopper des composants portables dployables sur AWS et Azure.
• Supporter lintgration de services tels que AWS Batch, Glue, S3, Lambda, EventBridge, etc.

Contexte ERP & retail

• Travailler avec des jeux de donnes ERP (Oracle), y compris des structures relationnelles complexes.
• Comprendre les besoins spcifiques des applications IA en analytique retail et supply chain.

Qualifications

Formation & exprience

• Master en Data Science, Informatique ou Gnie logiciel.
• 5+ ans dexprience en ingnierie des donnes cloud, infrastructure et dploiement.
• Exprience professionnelle antrieure avec des pipelines ou applications IA/ML fortement recommande.

Stack & outils (exprience requise)

• AWS (S3, Lambda, Glue, RDS, IAM, EventBridge), AWS Batch, Azure
• Snowflake, Oracle, SQL
• Python, PySpark, Docker, Kubernetes, Terraform
• Airflow, MLflow (pour le tracking), Git, pipelines CI/CD

Qualits recherches

• Autonomie, dbrouillardise et capacit piloter des solutions de lide la production.
• Grande rigueur et respect des bonnes pratiques de scurisation des donnes.
• Esprit collaboratif avec data scientists, product managers et architectes.
• Excellente communication crite et orale.

Informations complmentaires

• Mode hybride: 2jours/semaine au bureau de Montral
• Nous remercions toutes les personnes intresses; seules les personnes retenues seront contactes.

Rejoigneznous pour construire les fondations cloud de notre avenir IA!