Data and Software Engineer

General Bank of Canada (“GBC”) is a Schedule I Chartered Bank headquartered in Edmonton, Alberta, and part of the Wheaton Group. Since our entrepreneurial beginnings in the 1950s, we’ve grown into one of Canada’s fastest-growing small banks, delivering innovative financing solutions across the automotive, aviation, and commercial sectors.

At GBC, our values of Trust, Discipline, People First, and Innovation shape everything we do. Our agile, forward-thinking approach allows us to design smarter, more responsive banking solutions for a rapidly evolving digital world.

We’re proud to be certified as a Great Place to Work for seven consecutive years, reflecting our commitment to a culture where people feel supported, empowered, and inspired to do their best work.

Giving back is part of who we are. Since 1969, our long-standing partnership with United Way has supported meaningful volunteerism, fundraising, and community initiatives that make a lasting difference.

When you join General Bank of Canada, you become part of a team that’s not only shaping the future of banking but also strengthening the communities we serve. And yes, we genuinely love it here, and we think you will too.

The Opportunity

We’re looking for a Data and Software Engineer to join our Data, Technology and Innovation team and play an important role in our continued growth. At GBC, you won’t just fill a role; you’ll help build what’s next. This is a great opportunity to make a real impact, develop your skills, and grow your career in a dynamic, people-first environment.

The Data and Software Engineer is responsible for building and maintaining data pipelines, ELT/ETL processes, core banking smart contracts, and backend services and APIs that connect front-end applications to the enterprise integration layer, enabling efficient data access and integration within the enterprise data and application environment. This role takes a hands-on approach to developing data models and core banking product logic, ensuring data is well-structured, accurate, and accessible.

The Data and Software Engineer also plays a key role in data integration, full-stack application development, transformation, automation, monitoring, and deployment through CI/CD pipelines, supporting advanced analytics and core banking operations. Working closely with technical and business partners, this role gathers requirements, develops technical solutions, validates solution accuracy, and continuously improves data processes and technology capabilities across the organization.

Position Details

• Workplace Model: In-Office
• Working Conditions: Office environment with the ability to work remotely if required. Minimal physical effort including sitting, standing, and bending. Regular use of a computer and frequent interaction with employees and external contacts.
• Salary Range:The salary range for this position is $114,605.80 to $171,908.70. Compensation is commensurate with qualifications.
• Deadline to Apply: November 23, 2026.

Position Responsibilities

Data Pipeline Development

• Develop, test, and maintain scalable data pipelines and ELT/ETL solutions that support efficient, reliable, and accurate data processing.
• Use appropriate tools and cloud platforms, such as SQL, Python, Snowflake, and Azure to extract, clean, transform, and integrate data from multiple sources.
• Apply cloud data streaming architectures and patterns where appropriate.

Data Integration & Analysis

• Integrate internal and external data sources into the enterprise data environment and assess complex datasets for structure, quality, and suitability for integration.
• Develop reliable data extracts for internal and external consumers.
• Build reusable queries and datasets that enable self-service reporting and advanced analysis.

Data Governance & Modeling

• Develop data models and contribute to data governance frameworks that promote data quality, consistency, and compliance.
• Support data validation and reconciliation and adherence to established quality standards.
• Test, review, and validate newly developed views, data models, and data extracts to support accurate and reliable information.

ML Deployment

• Transition machine learning models from development into production environments.
• Automate and maintain feature stores that enable reusable machine learning features.
• Optimize storage, compute, and infrastructure costs associated with machine learning workflows.

Core Banking Development

• Develop, test, and maintain smart contracts and product logic on core banking platform (Thought Machine Vault).
• Ensure solutions align with product requirements and established architectural standards.

Application Development

• Develop, test, and maintain backend services and APIs that connect front-end applications with the enterprise integration layer, including technologies such as Azure Service Bus, Azure API Management, and Kafka.
• Contribute to complex front-end components, including integrations with backend and core banking systems.
• Review front-end code through pull requests to support reliability, security, performance, and adherence to development standards.

Deployment & Operational Support

• Deploy data, core banking, and application solutions through CI/CD pipelines, such as Azure DevOps and GitHub Actions, incorporating automated testing and version control.
• Follow established change management and security requirements throughout deployment.
• Monitor data, core banking, and application environments, investigate process failures, identify root causes, and implement corrective actions.
• Optimize system performance to improve reliability and scalability as organizational needs grow.

Collaboration

• Work with cross-functional teams to understand data and application needs and translate requirements into practical, scalable data and software solutions.
• Communicate technical solutions clearly to business and technical partners.
• Partner with internal and external teams to support seamless data and application integration and use agile practices to deliver solutions effectively.

Continuous Improvement & Innovation

• Stay current with emerging technologies and industry practices in data engineering, software development, and analytics.
• Identify and implement opportunities to improve delivery efficiency, technical capabilities, processes, and data and application solutions.

Requirements

What You Bring to the Table

Required Qualifications

• A bachelor’s degree in computer science, data engineering, software engineering, business, statistics, economics, finance, technology, or a related discipline. Demonstrated experience will also be considered.
• 3+ years of experience in data engineering, software development, or a related field, including hands-on experience with data integration, transformation, pipeline development, and full-stack application development.
• Proficiency in SQL, Python, and ELT/ETL tools used for data extraction, transformation, modeling, and extract development.
• Experience developing backend services and APIs using technologies such as .NET or Python, working with integration platforms such as Azure Service Bus, and using CI/CD pipelines.
• Strong software development capabilities across data-engineering and full-stack application development, including experience developing scalable data and software solutions within modern data and cloud platforms.
• Experience contributing to and reviewing front-end code through pull requests.
• Ability to analyze complex datasets, diagnose issues, evaluate risks, and develop practical, scalable solutions in complex or ambiguous situations.
• Understanding of governance, security, and compliance practices across data and application environments, including data integrity and reconciliation, secure development practices, and change management.
• Strong communication and collaboration skills, with the ability to translate technical requirements and complex concepts into clear, actionable solutions.
• A customer-focused and collaborative approach, with a commitment to integrity, accountability, transparency, and shared team goals.
• Ability to successfully fulfill the pre-employment screening requirements, including criminal and credit checks, as well as employment references from individuals who can provide direct insights into your performance and effectiveness in previous roles.

Preferred Qualifications

• Experience in financial services or another regulated industry.
• Relevant certifications in cloud platforms such as AWS, Azure, or GCP; Snowflake; core banking platforms such as Thought Machine Vault; or data engineering.
• Experience working with cloud-based data environments and modern data platforms.
• Experience with cloud-based data streaming architectures.
• Experience with front-end frameworks such as React.
• Experience developing product logic on core banking platforms, such as Thought Machine Vault smart contracts or Mambu.