Senior DataOps/Cloud Data Engineer

We are seeking an experienced Senior DataOps/Cloud Data Engineer to design, build, automate, and optimize enterprise-grade data pipelines and unified data platforms. In this role, you will lead the end-to-end development of ETL/ELT processes, modern Medallion architecture data lakehouses, and cross-platform data migrations using Databricks, Delta Live Tables (DLT), PySpark, and Azure Data Factory. Working closely with cross-functional technical teams in an Agile environment, you will implement DataOps practices, build CI/CD automation pipelines in Azure DevOps, execute database performance tuning, and establish secure data governance using Unity Catalog.

Location: Toronto, ON (Fully Onsite – 5 days/week required)

Duration: 6-month contract.



Advantages
Next-Gen Cloud Stack: Direct engineering with Databricks, Delta Live Tables, PySpark, Unity Catalog, and Microsoft Fabric.

Large-Scale Data Migration: Lead high-visibility enterprise data transformations and cross-platform migrations from legacy Oracle to Azure Cloud environments.

Automated DataOps & CI/CD: Hands-on ownership of automated pipeline creation, Git integrations, and continuous deployment workflows.

Dedicated Onsite Synergy: Collaborate directly alongside senior data leads, architects, and engineers in a focused 5-day per week Toronto workspace.



Responsibilities
ETL/ELT Engineering & Orchestration: Design, build, automate, and optimize complex data extraction, transformation, and loading (ETL/ELT) processes using Databricks, Delta Live Tables (DLT), and PySpark.

Unified Data Platform Architecture: Develop and manage unified enterprise data lakehouse platforms utilizing Databricks and Unity Catalog for governance, data security, and lineage.

Data Migration & Integration: Execute large-scale cross-platform data migrations and integrations, moving Very Large Datasets (VLD) from legacy relational systems (Oracle, SQL Server) to cloud destinations (Azure Data Lake, Databricks, Microsoft Fabric).

Cloud Pipeline Automation & CI/CD: Create, configure, and orchestrate Azure Data Factory copy pipelines and custom Databricks workflows with integrated Azure DevOps Git CI/CD deployment pipelines.

Database & Dimensional Modeling: Perform relational and dimensional data modeling (fact/dimension tables), schema design, advanced SQL querying (PL/SQL, T-SQL), and query optimization across cloud and on-premise relational databases.

DataOps & Performance Monitoring: Implement DataOps principles, continuous integration, automated data provisioning, performance monitoring, and query tuning to ensure high availability and scalability.

Technical Documentation & Collaboration: Partner with architects, developers, and business stakeholders to document technical designs, data flows, and operational procedures in an Agile delivery framework.



Qualifications
ETL/ELT & Databricks Mastery: Proven experience designing, building, automating, and optimizing complex ETL/ELT processes using Databricks, Delta Live Tables (DLT), and PySpark (Strictly Required).

Unified Data Governance: Demonstrated experience building unified data platforms using Databricks and Unity Catalog (Strictly Required).

Database & Advanced SQL Expertise: Strong background with relational databases (Oracle, MySQL, SQL Server), dimensional data modeling, and advanced SQL (PL/SQL, T-SQL) query tuning (Strictly Required).

Azure Pipeline & CI/CD Engineering: Proficient in creating Azure Data Factory pipelines and custom Databricks pipelines with Azure DevOps Git CI/CD integration (Strictly Required).

Enterprise Data Migration: Proven experience conducting data migration and integration across platforms (Oracle to Azure Data Lake, Databricks, or Microsoft Fabric) (Strictly Required).

Nice-to-Have Assets:
Experience designing Medallion architecture data lakehouses (Bronze, Silver, Gold layers).

Proficiency with scripting languages (Python, Unix shell, Scala) and cloud platforms (Azure, AWS, GCP).

Experience with disaster recovery, failover handling, and troubleshooting large-scale OLAP/OLTP systems.



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.