Data Engineer

Job Opportunity: Data Engineer 🌟
📅 Resume Due Date: Tuesday, December 16th, 2025 (5:00PM EST)
🆔 Job ID: 25-199
🔢 Number of Vacancies: 4
📊 Level: MP4
⏳ Duration: 11 Months
🕰️ Hours of work: 35 hours per week
📍 Location: CHQ, 1908 Colonel Sam Drive, Oshawa
🏠 Work Mode: Hybrid – 3 days remote

Job Overview

The Azure and Databricks Data Engineer is responsible for designing, building, and supporting data-driven applications that enable innovative, customer-centric digital experiences.
Working as part of a cross-discipline agile team, the role contributes to solving problems across business areas while building reliable, scalable, and performant data lake and data warehouse products.
Best practices in development, security, and accessibility are applied to deliver high-quality services. Modular ELT/ETL pipelines are designed and productionized, curated data models are built in collaboration with Data Architects, and secure handling of data in transit and at rest is ensured.
Responsibilities include cleaning and optimizing datasets, supporting BI analysts with dimensional modeling, troubleshooting ingestion and transformation issues, and collaborating with analysts, architects, and senior engineers to feed the enterprise data marketplace.
Process improvements such as automation, infrastructure optimization, and scalability enhancements are implemented. Tools in the Microsoft stack—Azure Data Factory, Data Lake, SQL Databases, Synapse Analytics, Databricks, Purview, and Power BI—are central to delivery.
Operating within an agile SCRUM framework, the engineer contributes to backlog development, builds data catalogs, and documents pipelines using source control. Optimized models are developed with Python, Spark, and SQL, consuming diverse data formats including XML, CSV, JSON, and REST APIs.
Additional duties include orchestrating pipeline execution, creating automation tooling, supporting CI/CD and DevOps pipelines, monitoring in-production solutions, and providing Tier 2 support. Role-based access controls are managed, automated testing is performed, and peer code reviews are conducted to ensure maintainable, high-quality solutions.

Qualifications

Completion of a four-year university program in computer science, software engineering, or related fields.
Experience designing and building data pipelines with Python, PySpark, SparkSQL, and SQL.
Hands-on expertise with Azure Data Factory, ADLS, Synapse Analytics, and Databricks.
Strong understanding of data structures, governance, and quality principles.
Effective communication skills to translate technical details for non-technical stakeholders.

To apply please send your resume to careers@cpus.ca or through the following link: https://lnkd.in/erbxUuqK