Technology Designer, Platform & DataOps

iA Financial Group•Montreal, QC

3d•Hybrid

About The Position

Build the future with us Do you want to play a strategic role in the design and evolution of modern, secure, and highly available data platforms? This role will allow you to directly contribute to the standardization and industrialization of DataOps and cloud practices within the organization. This position represents a great opportunity to showcase your skills and fully leverage your potential within a caring and reliable organization. Here, people and their development are at the heart of priorities, fostering an environment conducive to collaboration and innovation.

Requirements

Holds a degree in computer science, engineering, information systems, or any other relevant field.
Has 10 years of experience in development or design of data platforms, DataOps, or cloud.
Is recognized for their expertise in CI/CD, DataOps, and data platform automation.
Stands out for their mastery of cloud environments, particularly Google Cloud Platform (GCP).
Is recognized for their rigor, autonomy, and ability to solve complex problems.
Demonstrates a strong ability to collaborate with multidisciplinary business and IT teams.
Has significant experience with Terraform, Docker, and Kubernetes.
Has a good knowledge of ETL/ELT pipelines, analytics, and Big Data environments.
Has excellent command of the French language, both spoken and written.
Has an advanced level of English proficiency, as the person will be required to lead presentations, meetings, and produce documentation, as well as emails with internal and external partners on a weekly basis.

Responsibilities

Design, implement, and maintain robust CI/CD pipelines for data platforms and cloud resources.
Industrialize DataOps practices and standardize deployment models for data platforms.
Design and deploy data and cloud infrastructures using the Infrastructure as Code (Terraform) approach.
Define and implement high availability, resilience, and disaster recovery strategies.
Design and operate containerization and orchestration solutions based on Docker and Kubernetes.
Integrate containerized environments into CI/CD pipelines and DataOps practices.
Automate data and cloud operations to reduce manual interventions and operational risks.
Implement monitoring, remediation, and automated troubleshooting mechanisms to improve reliability and reduce MTTR.
Design and maintain ETL/ELT pipelines for large-scale data ingestion, transformation, and enrichment.
Integrate analytical components and, when required, machine learning-type processing.
Feed Business Intelligence tools and perform ad hoc analyses for troubleshooting and performance optimization.
Collaborate closely with business and IT teams to understand needs, define data and cloud strategies, and recommend appropriate architectures.
Act as a technical reference and advisor on best practices related to data platforms, DataOps, and cloud.