The Data Protection (DP) group executes the Firm’s Data Cybersecurity Strategy by designing, engineering, deploying, and operating enterprise-wide data security capabilities. Guided by architectural rigor, automation, and Agile delivery, the group ensures that users and business partners seamlessly adopt and effectively integrate core Data Protection Services controls across the organization.

Location: Montreal (Day 1 onboarding onsite/in office presence 3x/week)

Must have

- Scripting: Python, Linux Shell
- DevOps: Git, Jenkins Pipeline, Test Automation
- Orchestration: Docker, Kubernetes
- OS: Linux (in-depth), Windows
- Networking: network configuration and debugging
- Cloud: Azure Dev/DevOps, Public Cloud management
- Security Practices: Knowledge of critical cyber security controls
- AI Software Development Lifecycle (AI SDLC): Working knowledge of the secure and governed use of artificial intelligence across requirements, design, development, testing, deployment, monitoring, and continuous improvement, including appropriate human oversight.
- Willing to work in on-call rotation

Would Be Nice

- Cloud: M365, AWS, etc.
- Orchestration: Ansible, Terraform, Cloudify, other IaC
- SRE: Flux, Grafana, Splunk
- Agile: Jira
- Products: BigID, Securiti

Professional Skills

- Demonstrated experience working effectively within Agile delivery teams.




- Proven experience integrating products into enterprise environments, including the deployment and integration of open-source products and tools using DevOps methodologies.
- Working knowledge of IT Service Management principles and ITIL practices.
- Ability to acquire and apply knowledge of proprietary technologies within a complex, regulated environment.
- A self-directed approach, supported by demonstrable experience in the technical and application support of enterprise systems.
- Excellent written and verbal communication skills, together with a professional and collaborative working style.
- A solid automation and orchestration mindset, with a focus on reducing manual processes and enabling product squads to devote greater capacity to engineering activities.

Attributes

- A strong professional interest in automation, DevOps, and site reliability engineering.
- Comfort working within delivery models that use frequent, incremental code testing and deployment.
- A practical, hands-on approach to implementing DevOps processes from requirements analysis and test design through automation and results analysis.
- Accountability for the quality and timeliness of assigned deliverables.
- The ability to communicate material issues, risks, and progress updates accurately, clearly, and in a timely manner.

📌 DevOps Engineer (Montreal)
🏢 Randstad Enterprise
📍 Montreal