Sr. DevOps Engineer to support the deployment, monitoring, and automation of infrastructure and applications across cloud environment for a retail client

Our client is looking for a Sr. DevOps Engineer to support the deployment, monitoring, and automation of infrastructure and applications across cloud environment for a retail client.

Permanent, 3 days a week in midtown Toronto

Overview:

The DevOps Engineer, Cloud and Data Ops is responsible for supporting the deployment, monitoring, and automation of infrastructure and applications across a hybrid cloud environment. This role plays a pivotal role in the delivery and sustainment of scalable and secure systems that enable the organization’s growth and daily operations.

This position will be expected to provide internal client support across departments and teams. With a background in cloud infrastructure and automation, the DevOps Engineer, Cloud and Data Ops will be responsible for interpreting business needs, assessing data and infrastructure requisites, and implementing solutions to address non-standard issues while ensuring the company's values, goals, and principles are reflected in the delivery of technology solutions. The role will also spend time implementing changes, updates, or new releases to existing systems, assisting with the deployment of new platforms, and optimizing integrations across various business areas.

Must Have's:

• 5+ years experience in DevOps, cloud infrastructure, data architecture, or related fields
• Bachelor’s degree in computer science/engineering or relevant discipline or equivalent education and experience
• Strong experience with Microsoft Azure DevOps, CI/CD pipelines, and infrastructure automation
• Familiarity with scripting languages such as PowerShell or Python
• Experience working with SQL and supporting data movement or integration between systems
• Knowledge of security best practices for cloud and on-prem environments

Nice to Have's:

• API development is considered an asset
• Experience in supply chain or retail industries is considered an asset
• Ability to travel periodically within Canada (valid driver’s license and passport required)

Responsibilities:

• Monitor and manage Tableau Server performance, capacity planning and scaling
• Troubleshoot server and dashboard issues, resolving connectivity and performance concerns ensuring minimal downtime; maintain and validate data sources ensuring accuracy and consistency
• Oversee and maintain cloud and on-prem infrastructure, ensuring high availability and security of development, testing, and production environments
• Design, implement, and maintain CI/CD pipelines to support seamless deployment of applications and data workflows
• Manage access control and security compliance across DevOps tools and cloud environments
• Collaborate with IT teams to streamline release management, automation, and cloud operations
• Own and manage the data warehouse, ensuring data integrity, performance, and availability
• Design, implement, and optimize ETL processes using Microsoft Azure Data Factory and related technologies
• Support data integration initiatives, ensuring seamless data flow between ERP, business intelligence tools, and other business systems
• Identify and implement best practices for data governance, quality control, and performance optimization
• Work closely with the business intelligence personnel, coaching and mentoring on data modeling, query optimization, and analytics best practices
• Act as a subject-matter expert in DevOps and data architecture, guiding IT and business teams on technology decisions
• Mentor other IT staff, providing training on infrastructure management, DevOps processes, and best practices
• Provide strategic recommendations to senior leadership on technology improvements and innovations
• Collaborate with stakeholders to understand business needs and translate them into technical solutions
• Drive transparency, documentation, and structured processes across DevOps and data operations
• Support change management initiatives by facilitating smooth transitions in DevOps processes, infrastructure updates, and data architecture improvements, ensuring minimal business disruption
• Cross functionally identify opportunities for machine learning and assist to build AI driven solutions