Location: Oshawa, ON, Hybrid, 3 days remote, 2 days remote
Language: English, strong written and verbal communication skills required
Duration: 11-month contract
Background Check Requirement: Must be eligible to pass a graduated background check
Rates:$55-70/T4- $70-90/INC
Our client in the public sector is looking for experienced Azure and Databricks Data Engineers to help build and support modern, data-driven platforms that enable innovative, customer-centric digital experiences. This is a chance to contribute to large-scale data initiatives that directly support analytics, reporting, and digital services used across the organization.
You’ll join a collaborative, cross-functional agile team where data engineers, analysts, architects, and security partners work closely to solve complex problems together. Your work will help create trusted, high-quality data products that empower decision-making and support long-term innovation.
This opportunity offers exposure to enterprise-scale Azure environments and modern lakehouse architectures. You’ll work alongside experienced data professionals who value collaboration, knowledge sharing, and continuous improvement.
You’ll also benefit from a balanced work structure with a hybrid model, meaningful project ownership, and the chance to strengthen your skills across data engineering, governance, and DevOps practices in a supportive, people-first environment.
You’ll design, build, and support scalable ELT and ETL data pipelines using Azure and Databricks technologies.
In this role, you’ll develop reliable data lake and data warehouse products that support analytics, applications, and innovation.
You’ll collaborate with data architects and modelers to build curated, business-centric data models.
You’ll ensure data is secure, well-governed, and high quality, applying lineage, testing, and access controls throughout the lifecycle.
You’ll support BI and analytics teams by preparing and optimizing datasets for reporting and visualization.
You’ll troubleshoot pipeline performance, data accuracy, and ingestion issues in production environments.
You’ll contribute to agile delivery, documentation, peer code reviews, and continuous improvement initiatives.
5+ years of experience as a Data Engineer designing and building data pipelines
University degree in computer science, engineering, or a related data-focused discipline
Strong experience with Python, Spark, PySpark, SQL, and Azure Databricks
Hands-on knowledge of Azure Data Factory, ADLS, Synapse Analytics, and related Azure services
Experience working with data lakehouse and data warehouse architectures
Solid understanding of data governance, data quality, and performance optimization
Ability to clearly communicate technical concepts to non-technical stakeholders
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