Are you a seasoned Data Engineer with a passion for building scalable, cloud-native data pipelines and modernizing enterprise data platforms? This full-time contract role is ideal for professionals with strong Azure expertise, hands-on development experience, and a keen understanding of DataOps principles. The opportunity spans the full data engineering lifecycle, from ingestion to orchestration, in support of high-impact analytics, AI/ML, and reporting initiatives.
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Our Client is looking for a DataOps/Cloud Data Engineer for a 5 month onsite engagement in Toronto, with a focus on Azure Data Services, ADF, Databricks, and DevOps automation.
Advantages
đ§đ» Work directly on cloud-native platforms like Azure Synapse, Data Lake, and Databricks
đ ïž Lead end-to-end development of advanced data pipelines and architecture
đ Enable data-driven decision-making through well-governed and integrated data assets
đ Exposure to large-scale data migration and transformation initiatives
đ Contribute to enterprise-grade data security, privacy, and standards
đ Collaborate with strategic teams in analytics, ML, and product development
Responsibilities
âą Design and implement high-performance data pipelines using Azure Data Factory and Databricks Workflows
âą Automate and orchestrate ETL/ELT processes for structured, semi-structured, and unstructured data
âą Develop and optimize data ingestion, transformation, and provisioning pipelines
âą Collaborate with technical and business stakeholders to capture requirements and translate them into data solutions
âą Support cloud migration projects, including OLTP/OLAP workloads and large datasets
âą Troubleshoot pipeline failures, optimize performance, and ensure data accuracy
âą Contribute to metadata management, data cataloging, and lineage tracking
âą Enforce data governance, quality controls, and security standards across all data flows
âą Enable self-serve analytics and ML workloads through seamless data integration
âą Provide production support and participate in performance tuning activities
Qualifications
Must Have:
âą 5+ years of experience in data engineering and data modeling
âą Strong development experience with:
âą Azure Data Factory (ADF), Azure Databricks, Azure Synapse Analytics
âą Azure Data Lake, Azure SQL Database, Azure Storage
âą Python, Scala, and T-SQL
âą GitHub Actions or Azure DevOps for CI/CD and pipeline automation
âą Deep understanding of data warehousing, OLAP, star/snowflake schema design
âą Hands-on experience with DataOps practices and Agile/Scrum methodologies
âą Proficiency in ingestion, transformation, and provisioning across SaaS, PaaS, and IaaS
âą Experience with cloud-native services like DaaS, DBaaS, and DWaaS
Nice to Have:
𧱠Experience with infrastructure elements like Azure Key Vault, virtual machines, and disks
đ§ Familiarity with secure data exchange frameworks and performance monitoring tools
đ Knowledge of metadata management, data lineage, and ER/dimensional modeling
đ Experience with data security, privacy laws, and compliance frameworks
đ§Ș Exposure to AI/ML pipelines or real-time analytics environments
Summary
This is a technical role tailored for a data engineering professional passionate about cloud-first architecture, automation, and high-volume data transformation. The ideal candidate will thrive in an agile, performance-driven environment and bring a depth of Azure expertise to elevate data integration, governance, and provisioning efforts for enterprise-wide analytics and digital innovation.
If you are interested in this role, please apply online at www.randstad.ca. Qualified candidates will be contacted.
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.
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Are you a seasoned Data Engineer with a passion for building scalable, cloud-native data pipelines and modernizing enterprise data platforms? This full-time contract role is ideal for professionals with strong Azure expertise, hands-on development experience, and a keen understanding of DataOps principles. The opportunity spans the full data engineering lifecycle, from ingestion to orchestration, in support of high-impact analytics, AI/ML, and reporting initiatives.
Our Client is looking for a DataOps/Cloud Data Engineer for a 5 month onsite engagement in Toronto, with a focus on Azure Data Services, ADF, Databricks, and DevOps automation.
Advantages
đ§đ» Work directly on cloud-native platforms like Azure Synapse, Data Lake, and Databricks
đ ïž Lead end-to-end development of advanced data pipelines and architecture
đ Enable data-driven decision-making through well-governed and integrated data assets
đ Exposure to large-scale data migration and transformation initiatives
đ Contribute to enterprise-grade data security, privacy, and standards
đ Collaborate with strategic teams in analytics, ML, and product development
Responsibilities
...
âą Design and implement high-performance data pipelines using Azure Data Factory and Databricks Workflows
âą Automate and orchestrate ETL/ELT processes for structured, semi-structured, and unstructured data
âą Develop and optimize data ingestion, transformation, and provisioning pipelines
âą Collaborate with technical and business stakeholders to capture requirements and translate them into data solutions
âą Support cloud migration projects, including OLTP/OLAP workloads and large datasets
âą Troubleshoot pipeline failures, optimize performance, and ensure data accuracy
âą Contribute to metadata management, data cataloging, and lineage tracking
âą Enforce data governance, quality controls, and security standards across all data flows
âą Enable self-serve analytics and ML workloads through seamless data integration
âą Provide production support and participate in performance tuning activities
Qualifications
Must Have:
âą 5+ years of experience in data engineering and data modeling
âą Strong development experience with:
âą Azure Data Factory (ADF), Azure Databricks, Azure Synapse Analytics
âą Azure Data Lake, Azure SQL Database, Azure Storage
âą Python, Scala, and T-SQL
âą GitHub Actions or Azure DevOps for CI/CD and pipeline automation
âą Deep understanding of data warehousing, OLAP, star/snowflake schema design
âą Hands-on experience with DataOps practices and Agile/Scrum methodologies
âą Proficiency in ingestion, transformation, and provisioning across SaaS, PaaS, and IaaS
âą Experience with cloud-native services like DaaS, DBaaS, and DWaaS
Nice to Have:
𧱠Experience with infrastructure elements like Azure Key Vault, virtual machines, and disks
đ§ Familiarity with secure data exchange frameworks and performance monitoring tools
đ Knowledge of metadata management, data lineage, and ER/dimensional modeling
đ Experience with data security, privacy laws, and compliance frameworks
đ§Ș Exposure to AI/ML pipelines or real-time analytics environments
Summary
This is a technical role tailored for a data engineering professional passionate about cloud-first architecture, automation, and high-volume data transformation. The ideal candidate will thrive in an agile, performance-driven environment and bring a depth of Azure expertise to elevate data integration, governance, and provisioning efforts for enterprise-wide analytics and digital innovation.
If you are interested in this role, please apply online at www.randstad.ca. Qualified candidates will be contacted.
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.
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