We are seeking a highly accomplished Senior DataOps/Cloud Data Engineer for an enterprise-level contract opportunity based in Toronto. In this role, you will take on a premier data pipeline engineering, cloud data platform architecture, and DataOps automation capacity, specializing in designing, building, and optimizing enterprise-grade data lakes, data lakehouses, and continuous integration workflows.
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As a Senior DataOps/Cloud Data Engineer, you will bridge the gap between complex source systems, cloud data platforms, metadata governance frameworks, and downstream analytics consumers. Operating fully onsite in Toronto, you will lead the end-to-end implementation of scalable ETL/ELT pipelines, operationalize Medallion Architectures, automate data provisioning, and implement DataOps practices using Databricks, Delta Lake, and Azure Data Services. This position demands a technical data authority with extensive experience across cloud platforms, data modeling, API integrations, and database technologies who can ensure high-performance, secure, and reliable data delivery.
Location: Toronto, ON
Assignment Type: Onsite (5 days per week)
Contract Duration: 12-month contract (with potential for extension)
Advantages
Modern Cloud Data Stack: Build data pipelines using Databricks, Delta Lake, Databricks SQL, Azure Data Factory, and Microsoft Fabric.
Medallion Architecture Leadership: Operationalize structured, semi-structured, and unstructured data across Bronze, Silver, and Gold data lakehouse layers.
Automated DataOps & CI/CD: Drive deployment automation, automated data testing, continuous integration pipelines, and metadata collection.
Enterprise Modernization Impact: Lead large-scale data migrations, cloud transformations, and integration platforms like Informatica to operationalize common data models.
Responsibilities
Design, develop, automate, and optimize end-to-end data pipelines and integration flows connecting diverse source systems to enterprise data platforms.
Implement and configure modern cloud data platform components, data lakehouses, and Medallion Architecture frameworks utilizing Databricks and Delta Lake.
Build scalable ETL/ELT data ingestion, processing, and transformation workflows using Azure Data Factory and Informatica integration platforms.
Implement DataOps practices, including deployment automation, automated testing, performance monitoring, and continuous integration/continuous deployment (CI/CD) pipelines.
Operationalize common data models, enterprise metadata repositories, data lineage tracing, and automated metadata collection processes.
Perform data pipeline tuning, database optimization, and performance benchmarking across cloud Data as a Service (DaaS) and Data Warehouse as a Service (DWaaS) environments.
Support data migration, transformation, and conversion of large-scale OLAP and OLTP datasets to cloud platforms.
Collaborate with data architects, data modelers, and governance teams to enforce data security, access controls, privacy, and operational standards.
Troubleshoot complex data flow errors, pipeline bottlenecks, and platform integration issues to maintain service availability.
Maintain comprehensive technical documentation, data mapping specifications, architectural diagrams, and operational runbooks.
Qualifications
Core Technical & Data Engineering Requirements
Databricks & Lakehouse Architecture: Hands-on experience with Databricks, Delta Lake, Databricks SQL, and practical implementation of Medallion Architecture principles.
Azure Data Ecosystem: Direct experience building data solutions using Azure Data Services, Azure Data Factory, and cloud storage infrastructure.
Integration & Metadata Platforms: Proven experience with Informatica (or equivalent enterprise integration platforms) and experience operationalizing common data models and metadata repositories.
DataOps & CI/CD Automation: Strong experience implementing DataOps practices, test automation, data quality frameworks, and CI/CD deployment pipelines.
ETL/ELT & Data Modeling: Solid track record designing, building, and supporting scalable data pipelines, data warehouses, data lakes, and dimensional/fact models.
Programming & Query Languages: Proficiency in data engineering languages and tools (e.g., Python, SQL, Scala, PowerShell) for automation, scripting, and pipeline development.
Preferred Assets & Specialized Technologies
Modern Governance & Fabric Tools: Experience or familiarity with Microsoft Purview, Microsoft Fabric, or semantic/graph data repositories is a strong asset.
Public Sector Context: Prior experience delivering data platform engineering solutions within public sector environments is considered an asset.
Soft Skills & Delivery Attributes
Analytical Problem Solving: Superior diagnostic capabilities to troubleshoot complex data flows, performance bottlenecks, and system integration errors under tight timelines.
Communication & Collaboration: Excellent written and verbal communication skills with a proven track record of collaborating effectively across multidisciplinary teams.
Summary
If you're interested in the "Senior DataOps/Cloud 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.
This posting is for existing and upcoming vacancies.
show more
We are seeking a highly accomplished Senior DataOps/Cloud Data Engineer for an enterprise-level contract opportunity based in Toronto. In this role, you will take on a premier data pipeline engineering, cloud data platform architecture, and DataOps automation capacity, specializing in designing, building, and optimizing enterprise-grade data lakes, data lakehouses, and continuous integration workflows.
As a Senior DataOps/Cloud Data Engineer, you will bridge the gap between complex source systems, cloud data platforms, metadata governance frameworks, and downstream analytics consumers. Operating fully onsite in Toronto, you will lead the end-to-end implementation of scalable ETL/ELT pipelines, operationalize Medallion Architectures, automate data provisioning, and implement DataOps practices using Databricks, Delta Lake, and Azure Data Services. This position demands a technical data authority with extensive experience across cloud platforms, data modeling, API integrations, and database technologies who can ensure high-performance, secure, and reliable data delivery.
Location: Toronto, ON
Assignment Type: Onsite (5 days per week)
...
Contract Duration: 12-month contract (with potential for extension)
Advantages
Modern Cloud Data Stack: Build data pipelines using Databricks, Delta Lake, Databricks SQL, Azure Data Factory, and Microsoft Fabric.
Medallion Architecture Leadership: Operationalize structured, semi-structured, and unstructured data across Bronze, Silver, and Gold data lakehouse layers.
Automated DataOps & CI/CD: Drive deployment automation, automated data testing, continuous integration pipelines, and metadata collection.
Enterprise Modernization Impact: Lead large-scale data migrations, cloud transformations, and integration platforms like Informatica to operationalize common data models.
Responsibilities
Design, develop, automate, and optimize end-to-end data pipelines and integration flows connecting diverse source systems to enterprise data platforms.
Implement and configure modern cloud data platform components, data lakehouses, and Medallion Architecture frameworks utilizing Databricks and Delta Lake.
Build scalable ETL/ELT data ingestion, processing, and transformation workflows using Azure Data Factory and Informatica integration platforms.
Implement DataOps practices, including deployment automation, automated testing, performance monitoring, and continuous integration/continuous deployment (CI/CD) pipelines.
Operationalize common data models, enterprise metadata repositories, data lineage tracing, and automated metadata collection processes.
Perform data pipeline tuning, database optimization, and performance benchmarking across cloud Data as a Service (DaaS) and Data Warehouse as a Service (DWaaS) environments.
Support data migration, transformation, and conversion of large-scale OLAP and OLTP datasets to cloud platforms.
Collaborate with data architects, data modelers, and governance teams to enforce data security, access controls, privacy, and operational standards.
Troubleshoot complex data flow errors, pipeline bottlenecks, and platform integration issues to maintain service availability.
Maintain comprehensive technical documentation, data mapping specifications, architectural diagrams, and operational runbooks.
Qualifications
Core Technical & Data Engineering Requirements
Databricks & Lakehouse Architecture: Hands-on experience with Databricks, Delta Lake, Databricks SQL, and practical implementation of Medallion Architecture principles.
Azure Data Ecosystem: Direct experience building data solutions using Azure Data Services, Azure Data Factory, and cloud storage infrastructure.
Integration & Metadata Platforms: Proven experience with Informatica (or equivalent enterprise integration platforms) and experience operationalizing common data models and metadata repositories.
DataOps & CI/CD Automation: Strong experience implementing DataOps practices, test automation, data quality frameworks, and CI/CD deployment pipelines.
ETL/ELT & Data Modeling: Solid track record designing, building, and supporting scalable data pipelines, data warehouses, data lakes, and dimensional/fact models.
Programming & Query Languages: Proficiency in data engineering languages and tools (e.g., Python, SQL, Scala, PowerShell) for automation, scripting, and pipeline development.
Preferred Assets & Specialized Technologies
Modern Governance & Fabric Tools: Experience or familiarity with Microsoft Purview, Microsoft Fabric, or semantic/graph data repositories is a strong asset.
Public Sector Context: Prior experience delivering data platform engineering solutions within public sector environments is considered an asset.
Soft Skills & Delivery Attributes
Analytical Problem Solving: Superior diagnostic capabilities to troubleshoot complex data flows, performance bottlenecks, and system integration errors under tight timelines.
Communication & Collaboration: Excellent written and verbal communication skills with a proven track record of collaborating effectively across multidisciplinary teams.
Summary
If you're interested in the "Senior DataOps/Cloud 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.
This posting is for existing and upcoming vacancies.
show more
