Data Engineer focused on analytics and data pipeline development for network optimisation. Collaborating with teams to deliver high - quality data solutions with Python and SQL.
About the role
- Senior Cloud Data Engineer building cloud infrastructure for AI/ML product pipelines. Leading projects from data ingestion to model deployment in hybrid work model.
Responsibilities
- Design and build scalable, secure, multi-tenant cloud data pipelines on AWS and Azure.
- Implement ETL/ELT pipelines and robust APIs to move and access data between Oracle, AWS and Snowflake (ERP→cloud, cloud→ERP, intra-cloud).
- Leverage AWS services (Glue, Lambda, S3, RDS, EventBridge), AWS Batch, Azure components, and orchestration tools (Airflow, Kedro) to ensure resilience and maintainability, emphasizing modularity and reusability.
- Automate infrastructure provisioning with Terraform/OpenTofu; manage CI/CD pipelines using Jenkins, GitHub Actions, or ArgoCD.
Requirements
- Master's degree in Data Science, Computer Science, or Software Engineering
- 5+ years of experience in cloud data engineering, infrastructure and deployment
- Prior professional experience with AI/ML pipelines or applications strongly preferred
- 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
Benefits
- Hybrid work: 2 days per week in the Montreal office
Job title
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