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About the Role

The Data Engineering Developer drives the technical detail design, development, and optimization of data products, ensuring the reliability and performance of ETL processes. This role involves designing and developing complex data pipelines, implementing solutions that comply with architectural requirements, and collaborating with key partners to meet business objectives.

Responsibilities

• Ensure the stability, availability, and reliability of critical Data & Analytics platforms by proactively supporting KTLO and AMTS objectives.
• Reduce productivity incidents and service disruptions through proactive monitoring, automation, root cause analysis, and continuous improvement initiatives.
• Design and develop supportable data solutions that incorporate operational readiness requirements, including monitoring, alerting, recovery procedures, and runbooks.
• Partner with delivery teams to ensure seamless transition of new solutions into support, with complete documentation, dependency mapping, and support processes.
• Drive platform health and operational excellence by identifying and addressing technical debt, recurring issues, and performance bottlenecks.
• Improve application and data pipeline resiliency through automation, self-healing capabilities, capacity management, and proactive risk mitigation.
• Support incident, problem, and change management activities by participating in troubleshooting, service restoration, and corrective action implementation.
• Leverage DevOps platforms (e.g., GitHub) and Infrastructure as Code practices (e.g., Terraform) to automate deployments, improve operational reliability, and ensure consistent, supportable production environments.

Requirements

• Around 5 years of experience in data engineering with experience in building modern data platforms and data products.
• 3+ years of experience with distributed computing (ex. Spark) and infrastructure as code (ex. Terraform).
• 3+ years of experience designing and implementing scalable, cloud-based data solutions (Azure preferred).
• Good understanding of data modeling, ETL processes, data warehousing concepts, and best practices in data engineering and analytics.
• Good knowledge of cloud security and networking is an asset.
• Vast hands-on experience with the following Azure PaaS is an asset: Azure Data Lake Storage (ADLS), Azure Databricks, Microsoft Fabric, Azure Data Factory (ADF), Azure Synapse, Event Hub, API Management (APIM), Azure Key Vault, Azure SQL, REST API and Purview.
• Have a good understanding of the backup, disaster recovery, and data recovery strategy and execution with the above services.
• Ability to interact with peers and stakeholders to define and drive product and business impact.
• Innovative mindset to improve operational efficiencies and ability to influence change, with a primary focus on client needs.
• Critical thinking skills to recognize assumptions, evaluate arguments, draw conclusions and proactively propose solutions.
• Strong communication skills to clearly convey messages and explore diverse points of view.
• Ability to build trusting relationships and provide guidance to support the development of colleagues.
• Will travel occasionally.
• Will be subject to a Background check as a condition of employment, in the event you are the successful candidate.
• Will participate in a rotational on-call support schedule, including coverage outside of standard business hours, to ensure the timely resolution of production issues and service disruptions.

Skills

• Spark
• Terraform
• Azure
• Data Modeling
• ETL processes
• Data Warehousing
• Data Engineering
• Analytics
• Cloud Security
• Networking
• Azure Data Lake Storage (ADLS)
• Azure Databricks
• Microsoft Fabric
• Azure Data Factory (ADF)
• Azure Synapse
• Event Hub
• API Management (APIM)
• Azure Key Vault
• Azure SQL
• REST API
• Purview
• Backup
• Disaster Recovery
• Data Recovery
• DevOps
• GitHub
• Infrastructure as Code

Location

• Hybrid

Work Type

• Regular Full-Time
• Hybrid (2 days in office)

Experience Level

• Around 5 years of experience in data engineering
• 3+ years of experience with distributed computing
• 3+ years of experience designing and implementing scalable, cloud-based data solutions

Salary/Compensations

• $69,660 to $116,100

Benefits

• Training and development opportunities
• Flexible work options
• Paid time off
• Holistic approach to well-being, with physical and mental health programs
• Supportive workplace culture
• Paid volunteer days
• Competitive salary and incentive programs
• Comprehensive total rewards package
• Group retirement savings plans
• Pension and benefits (e.g., health and wellness, dental, disability and life coverage)
• Mental health support
• Employee assistance program

About the Company

• CGL is a leading Canadian financial services co-operative committed to being a catalyst for a sustainable and resilient society.
• The Information Technology team aspires to be a leader in applying technology to power business strategies.
• We connect concepts with solutions to create value and efficiencies for our clients, employees, and communities.
• Our success is driven by our skilled and diverse team who are passionate about excellence, innovation, and agility.