Senior Software Engineer – Cloud & Data Platforms

Duration: 12 months- Potential for extension or conversion based on business needs

Location: Toronto preferred; Waterloo also considered

Work Arrangement: Hybrid, onsite 2 days per week (3 days optional)

About the Team

The successful candidate will join the Data & Digital team within Engineering, Innovation & Architecture (EIA). The team consists of junior and senior developers, a Scrum Master, and technical leadership working closely with AI and Operations teams. The group owns, supports, and develops applications that power enterprise data platforms, analytics ecosystems, and emerging AI-enabled solutions. Many current and future initiatives involve modernizing applications, developing APIs, and integrating AI capabilities into business workflows.

JOB DESCRIPTION

Key Responsibilities:

Software Development & Engineering:

Design, develop, test, deploy, and support applications, APIs, and cloud-native solutions.

Participate in application modernization, code reviews, testing, and production support activities.

Troubleshoot complex application and integration issues and implement sustainable solutions.

Cloud Engineering & DevOps:

Build and maintain CI/CD pipelines, Infrastructure as Code, and deployment automation frameworks.

Automate infrastructure provisioning, application deployments, monitoring, and operational processes.

Improve platform reliability, scalability, security, and operational efficiency through automation and DevOps practices.

Data Platform & Analytics:

Support and enhance modern data and analytics platforms, including Snowflake and related technologies.

Collaborate with data engineers to support data ingestion, transformation, orchestration, and consumption patterns.

Assist with data platform administration, monitoring, troubleshooting, and performance optimization activities.

Security, Governance & Operations:

Implement security, access management, monitoring, and governance controls across applications and platforms.

Participate in incident management, root cause analysis, vulnerability remediation, and operational support activities.

Ensure solutions comply with enterprise architecture, security, and governance standards.

Collaboration & Technical Leadership:

Partner with architects, product owners, technical program managers, engineers, and business stakeholders.

Contribute to engineering best practices, reusable solutions, and continuous improvement initiatives.

Collaborate with enterprise technology teams to develop scalable and shared platform capabilities.

Critical Skills / Must-Haves:

5+ years of experience in software development, cloud engineering, DevOps, or data engineering.

3+ years of hands-on development experience using:

• C#
• .NET / .NET Core
• Python
• SQL
• Blazor or similar web application frameworks.

Proven experience designing, developing, deploying, and supporting enterprise applications and APIs in production environments.

Strong understanding of software engineering principles, application architecture, and cloud-native development patterns.

Hands-on experience building and maintaining CI/CD pipelines using Azure DevOps, Azure Pipelines, GitHub Actions, or similar tools.

Experience working with AWS services, including:

• EC2
• S3
• RDS
• EKS
• IAM
• CloudWatch.

Experience with Docker and Kubernetes/containerized application deployments.

Familiarity with Snowflake or comparable cloud-based data and analytics platforms.

Required Soft Skills

• Strong analytical thinking and problem-solving skills.
• Experience supporting and troubleshooting applications in production environments.
• Strong understanding of modern software development practices and SDLC methodologies.
• Excellent verbal and written communication skills.
• Ability to gather requirements and ask thoughtful discovery questions before proposing solutions.
• Strong stakeholder engagement and collaboration abilities.
• Ability to manage multiple priorities and projects simultaneously.
• Proactive, curious, and self-motivated approach to continuous improvement.
• Comfortable sharing opinions, providing recommendations, and participating in technical discussions.

Nice-to-Haves:

1. AI engineering, AI application development, or intelligent automation experience. Candidates who have contributed to AI-enabled solutions will be highly regarded.
2. Experience supporting self-service analytics, data products, or data marketplace initiatives.
3. Experience with Azure DevOps, GitHub Actions, Docker, Kubernetes, and modern platform engineering tools.
4. Experience working within financial services, insurance, asset management, or other regulated industries.
5. Working knowledge of PostgreSQL or other relational database technologies.
6. Familiarity with Power BI, Tableau, and modern analytics technologies.
7. Exposure to DevSecOps tools such as Snyk, Checkmarx, or similar security technologies.
8. Experience with mentoring developers or providing technical leadership within agile teams.

Education:

• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline preferred.
• Equivalent combinations of education, engineering-focused training, and relevant industry experience will also be considered.

Describe Your Top Performer: The ideal candidate combines strong technical depth with leadership and business acumen. They take time to fully understand requirements before designing solutions, ask insightful questions, proactively identify opportunities for improvement, and can independently architect and implement scalable applications. AI experience is a strong differentiator, but equally important are curiosity, initiative, adaptability, and the ability to collaborate effectively across multiple projects and stakeholder groups. The ideal candidate will also be comfortable mentoring others, driving technical discussions, and influencing solution direction.