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We are seeking a highly accomplished Senior Data Engineer for an enterprise-level contract opportunity based in Toronto. In this role, you will take on a key data engineering, analytics architecture, and business intelligence capacity, specializing in supporting, building, and optimizing enterprise data pipelines and analytics-ready datasets.
As a senior data engineer, you will bridge the gap between complex raw data sources, data lakes, structured data warehouses, and downstream reporting solutions. Operating within a hybrid work model in Toronto, you will design robust integration packages using SSIS and Azure Data Factory, write advanced database objects, implement data quality framework controls, and ensure all deliverables align with modern design methodologies and documentation standards. This position demands a technical data authority with extensive Microsoft Azure and SQL Server experience who can analyze complex data challenges, communicate clear solutions, and drive data-driven insights.
Location: Toronto, ON
Assignment Type: Hybrid (Minimum 2 days per week onsite)
Contract Duration: 12-month contract
Advantages
Modern Cloud Stack: Hands-on engineering across Azure Data Factory, Azure Synapse, SQL Data Warehouse, and Azure DevOps CI/CD pipelines.
Enterprise Data Scope: Design and maintain large-scale enterprise data warehouses, data marts, and data lakes.
End-to-End Analytics Ownership: Own full-lifecycle data pipelines, from ETL/ELT package development to data modeling and quality management.
Flexible Hybrid Setup: Enjoy a balanced working arrangement with predictable onsite days at a central Toronto office location.
Responsibilities
Design, build, test, document, and maintain enterprise data integration packages utilizing SSIS and Azure Data Factory (ADF).
Author and optimize complex T-SQL queries, stored procedures, views, triggers, and indexes across Azure Synapse, Azure SQL, and SQL Server platforms.
Assist in the architectural data modeling and design of enterprise data warehouses, data marts, and data lake storage structures.
Develop, implement, and monitor robust data quality, data cleansing, and data stewardship processes to ensure data accuracy and integrity.
Collaborate closely with business analysts and cross-functional project teams to translate business requirements into detailed technical specifications.
Perform advanced data analysis to extract actionable data-driven insights and support business intelligence reporting requirements.
Configure, maintain, and optimize automated CI/CD release pipelines using Azure DevOps.
Conduct unit testing, provide technical support across QA and User Acceptance Testing (UAT) phases, and prepare implementation plans.
Author comprehensive technical design documents, system functional specifications, and operational runbooks.
Research, propose, and share technical solutions and workflow improvements while conducting knowledge transfer sessions with team members.
Qualifications
Core Requirements & Technical Expertise
Data Engineering Experience: Minimum 5+ years of dedicated experience in database development or data engineering for enterprise-level solutions.
Integration & Cloud Tooling: Hands-on experience developing with SSIS and/or Microsoft Azure Data Factory (ADF) alongside related Azure platform services.
Data Warehouse Platforms: Demonstrated experience working with Microsoft Azure Synapse, SQL Data Warehouse, and SQL Server (2016 or later).
DevOps Pipelines: Direct experience configuring and managing CI/CD deployment pipelines within Azure DevOps.
Data Architecture & Modeling: Expert understanding of enterprise-scale Data Warehouse (DW) and Business Intelligence (BI) implementations, including data lake design and data modeling techniques.
Education: University degree in Computer Science, or equivalent combined with directly related technical experience.
Preferred Experience & Assets
Visualization Tools: Hands-on experience developing reports and dashboards using Microsoft Power BI or similar data visualization tools is an asset.
Data Governance: Practical knowledge of data quality control frameworks, data cleansing practices, and data stewardship standards.
Soft Skills & Delivery Attributes
Analytical Problem-Solving: Superior analytical capabilities to solve complex data challenges, optimize package performance, and provide accurate work estimates.
Communication & Collaboration: Excellent verbal, written, and interpersonal skills to articulate technical designs clearly and collaborate with cross-functional teams.
Summary
If you're interested in the "Senior Data Engineer" role based in Toronto, we encourage you to apply online at www.randstad.ca.
Only qualified candidates will be contacted for the next steps. We look forward to hearing from you!
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
