Data Engineer

🌟 Job Opportunity: Data Engineer 🌟
📅 Resume Due Date: Monday, July 27th, 2026 (5:00PM EST)
🆔 Job ID: 25-199
🔢 Number of Vacancies: 2
📊 Level: MP4
⏳ Duration: 11 Months
🕰️ Hours of work: 35 hours per week
💵 Hourly Range: $90-$95
📍 Location: CHQ 1908 Colonel Sam Drive, Oshawa, Ontario
🏠 Work Mode: Hybrid, 3 days remote per week

Job Overview

– As an Azure and Databricks Data Engineer, you will be responsible for designing, building, and supporting data-driven applications that enable innovative, customer-centric digital experiences.
– Work as part of a cross-discipline agile team to solve problems across all business areas and deliver reliable, supportable, and performant data lake and data warehouse products.
– Responsibilities include building modular and scalable data ELT/ETL pipelines and data infrastructure using a wide range of organizational data sources.
– Develop curated common data models that provide an integrated, business-centric single source of truth for business intelligence, reporting, and downstream system use.
– Work closely with infrastructure, cyber teams, Senior Data Developers, Data Architects, Business Analysts, Data Scientists, and Data Analysts to ensure data security, quality, lineage, and optimized performance throughout the data integration cycle.
– Support data visualization and reporting through dimensional data modeling and aggregation optimization methods. Troubleshoot ingestion, transformation, pipeline performance, data accuracy, and integrity issues while identifying opportunities to automate manual processes and improve scalability.
– Utilize Microsoft technologies including Azure Data Factory, Azure Data Lake, Azure SQL Databases, Azure Synapse Analytics, Azure Databricks, Microsoft Purview, and Power BI. Develop optimized data pipelines and models using Python, Spark, and SQL while consuming data sources including XML, CSV, JSON, REST APIs, and other formats.
– Implement data orchestration, role-based access controls, automated testing, source control, CI/CD pipelines, DevOps practices, and peer code reviews to support reliable enterprise data products.

Qualifications

– Requires completion of a four-year university education in computer science, computer/software engineering, data engineering, data analysis, artificial intelligence, or machine learning.
– Experience designing and building data pipelines, Python, PySpark, SparkSQL, Azure Data Factory, ADLS, Synapse Analytics, Databricks, Data Lakehouses, and Data Warehouses required.
– Strong understanding of data structures, processing frameworks, data governance, data quality principles, and effective communication skills to translate technical details to non-technical stakeholders.

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