Join one of Canada’s fastest-growing companies and be part of something extraordinary – welcome togoeasy Atgoeasy, our people and culture are at the heart of everything we do, and we’re proud to be recognized for it. We’ve earned prestigious accolades such asWaterstone Canada’s Most Admired Corporate Cultures ,Canada’s Top Growing Companies , and theTSX30 , highlighting us as one ofthe top performers on the TSX. We’re also honoured to be named a Greater Toronto Top Employer and recognized by Great Place to Work® as having the Best Workplaces for Women & Most Trusted Executive Teams , and included on TIME Magazine’s 2025 list of Canada’s Best Companies . These honours reflect our commitment to fostering an inclusive, high-performance culture where talent thrives and innovation drives us forward.

As one of Canada’s leading alternative consumer lenders, we’re passionate about helping everyday Canadians create a brighter future. Our vision is to provide a path to a better tomorrow, today. We offer a full range of products, including non-prime leasing, unsecured and secured loans, and point-of-sale financing through easyhome ,easyfinancial , andLendCare .

If you're seeking an exciting, high-growth setting where your contributions truly matter, we want to hear from you Join us, and together, let's create a future of financial empowerment.

The Data Operations Engineer is responsible for supporting, maintaining, and continuously improving goeasy's enterprise data platform. This role focuses on ensuring the reliability, performance, and operational health of production data services across Azure Databricks, Azure Data Factory (ADF), SQL Server, Enterprise Data Warehouse (EDW), and Managed File Transfer (SFTP)



platforms.

Working under the guidance of the Data Operations Team Lead, the successful candidate will support business-critical data workloads, troubleshoot production issues, onboard new data sources, deliver data and reporting requests, and contribute to the ongoing evolution of the organization's data ecosystem.

What will you be doing?

- Support and maintain production data workloads across Azure Databricks, Azure Data Factory, Azure Data Lake Storage, SQL Server, Enterprise Data Warehouse, and Managed File Transfer platforms.
- Support, maintain, and enhance existing SSIS packages and ETL processes while contributing to the modernization of data integration workloads using Azure Data Factory and Databricks.
- Monitor and troubleshoot data pipelines, workflows, integrations, and batch processing activities to ensure reliable and timely delivery of data.
- Investigate and resolve production incidents, job failures, data quality issues, performance bottlenecks, and integration challenges.
- Analyze and deliver ad-hoc data requests such as small enhancements and reporting requirements in collaboration with BI, Data Engineering and business stakeholders.
- Onboard new data sources and integrations from enterprise applications, databases, APIs, vendor platforms, and file-based interfaces.




- Support the ongoing evolution and optimization of the Enterprise Data Warehouse and enterprise reporting platforms.
- Perform SQL development, troubleshooting, and operational support activities across enterprise SQL Server environments.
- Participate in root cause analysis and continuous improvement initiatives to reduce recurring operational issues.
- Automate repetitive processes and operational tasks using scripting and cloud-native technologies.
- Collaborate with Data Engineering, BI, Infrastructure, Cloud Engineering, and Security teams to ensure reliable and supportable solutions.
- Participate in production deployments and validation activities, including outside of business hours.
- Ensure solutions comply with security, governance, and change management standards.

What experience do you have?

- Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent practical experience.
- 2-4 years of experience supporting and developing enterprise data solutions, including data warehouses, operational data stores, data integration platforms, and cloud-based data environments.
- Hands-on experience with Azure Databricks and strong SQL development skills, including building and supporting solutions on Microsoft SQL Server.
- Experience working with ETL/ELT processes, data warehousing concepts, data quality practices, and enterprise data integration frameworks.
- Experience supporting APIs, file-based integrations, Managed File Transfer (SFTP) solutions, and upstream/downstream system integrations.
- Proven ability to troubleshoot and resolve production incidents, batch processing

📌 Data Operations Engineer (Mississauga)
🏢 goeasy
📍 Mississauga