Senior Cloud Data Engineer | Ingnieure senior en donnes Cloud

Jesta I.S.; Montreal; Hybrid; CAD 100,000 - 130,000; Full time

Job summary

A leading technology firm in Montreal is seeking a Senior Cloud Data Engineer to lead the development of cloud infrastructure for AI/ML product pipelines. The ideal candidate should have a Master's degree in Data Science or a related field and 5+ years of experience in cloud data engineering. Responsibilities include designing and building data pipelines in AWS and Azure, implementing ETL processes, and supporting AI/ML workflows. The role involves hybrid work with 2 days in the office.

Benefits

Hybrid work model

Opportunity to lead AI projects

Collaborative workplace

Qualifications

• 5+ years of experience in cloud data engineering, infrastructure, and deployment roles.
• Prior experience with AI/ML pipelines or applications is strongly preferred.
• Strong understanding of cloud services and data management.

Responsibilities

• Architect and build scalable, secure, multi-tenant cloud data pipelines in AWS and Azure.
• Implement robust ETL/ELT pipelines to move and access data across platforms.
• Build infrastructure to support AI/ML workflows and enable model deployment.

Skills

Cloud data engineering

Problem-solving

Collaboration

Attention to detail

Education

Masters degree in Data Science, Computer Science, or Software Engineering

Tools

AWS

Azure

Python

Docker

Terraform

Kubernetes

Job description

Job Description

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!

propos du poste

Nous recrutons une Senior 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!