Data Analyst - Intermediate Location: Toronto, ON

Onsite Flexibility: Hybrid — 1 day onsite every 4th Friday

Contract Details Position Type: Contract Contract Duration: 6 months (with potential for extension) Pay Rate: C$55.00–C$67.00 / Hour (CAD) Shift / Schedule: Monday–Friday, 9:00 AM – 5:00 PM, 37.5 hours/week

Job Summary The Intermediate Data Analyst will support the HR Technology Team by designing, developing, and maintaining Azure Databricks–based ETL solutions. The role involves supporting complex HR technology projects, integrating data across multiple back-end systems and SaaS platforms, and contributing to the modernization of existing data workflows. The contractor will work closely with internal stakeholders and technical teams to ensure reliable, scalable, and efficient HR data solutions.

Key Responsibilities Design, develop, and maintain Azure Databricks–based ETL solutions Support complex HR technology projects Integrate data across multiple back-end systems and SaaS platforms Contribute to the modernization of existing data workflows Work closely with internal stakeholders and technical teams to ensure reliable, scalable, and efficient HR data solutions

Required Skills 3–5 years of Data Analytics / Developer experience 3 years of experience with Azure Databricks Experience working with Azure-based data platforms Strong analytical and problem-solving skills Clear communication and ability to work with technical and non-technical stakeholders Adaptability in a fast-paced, enterprise environment Team-oriented with the ability to work independently Willingness to learn and adapt to evolving HR technology platforms

Preferred Skills Experience with ServiceNow / Jira Informatica (not a deciding factor) AutoSys Feedhub integration

Medical, Vision, and Dental Insurance Plans 401k Retirement Fund

Important Notes The hiring manager is seeking candidates who can clearly articulate what they personally built, how they delivered it, and the technical decisions they made — candidates with primarily support-oriented Databricks experience are not a fit for this role. Candidates must demonstrate hands-on development experience within Databricks (active building and developing solutions), not merely supporting or monitoring existing environments. Core Databricks and data engineering fundamentals are expected for a mid-level resource with 3–5 years of relevant experience; gaps in these areas have been a disqualifying factor in prior interviews. Candidates should be prepared to discuss practical experience with building data pipelines, working with data lakes, and developing SQL-based solutions using specific examples from their own work. Experience level required: 3–5 years only; more senior profiles are not a fit. Interview process: 2 interviews conducted by the hiring manager.

About the Client This client is a large, full-service multinational financial institution offering a comprehensive range of banking, wealth management, and capital markets products and services, serving millions of clients across its home market and operating internationally with significant commercial and investment banking presence in the United States and other global markets. The organization employs professionals across data engineering, technology, business analysis, enterprise programs, and capital markets functions who collaborate within a structured, enterprise-scale environment. It is recognized for its commitment to inclusion and diversity, competitive compensation, and genuine opportunities for career development — making it a strong destination for professionals seeking stability and structured growth within a major financial institution.

About GTT GTT is a minority-owned staffing firm and a subsidiary of Chenega Corporation, a Native American-owned company in Alaska. We highly value diverse and inclusive workplaces and support Fortune 500 organizations across banking, financial services, technology, life sciences, biotech, utilities, and retail sectors throughout the U.S. and Canada.

Job Number: 26-08430 Industry: Data & Analytics

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