Data Engineer (Azure Data Factory & Databricks Focus)

Now Hiring: Data Engineer (Azure Data Factory & Databricks Focus)
📍 Location: Oshawa – Hybrid (3 days remote / 2 days on‑site)
🕒 Contract Duration: 11‑Month Contract | 35 Hours/Week
💵$90-$95/hour
👥 Vacancies: 2
📅 Resume Due Date: Wednesday, April 1, 2026 – 5:00 PM EST

About the Role
We are seeking hands‑on Data Engineers with strong, practical experience building data pipelines using Azure Data Factory and Databricks. We are specifically looking for professionals who have designed, built, and deployed new data pipelines end‑to‑end in Azure environments.

🚨 Critical Must‑Have Experience
Proven experience building new data pipelines using:
Azure Data Factory (ADF) for orchestration
Azure Databricks (Spark / PySpark) for transformations
Candidates without hands‑on pipeline development experience in ADF and Databricks will not be considered.

Key Responsibilities
Design, develop, and productionize modular, scalable ELT/ETL pipelines using Azure Data Factory and Databricks
Build and maintain data lake and data warehouse solutions supporting analytics, applications, and innovation
Cleanse, transform, and optimize large datasets using Python, PySpark, Spark SQL, and SQL
Develop curated, business‑centric common data models in collaboration with Data Architects and Data Modelers
Implement data quality, lineage, and governance controls throughout the data lifecycle
Ingest data from multiple sources including CSV, JSON, XML, REST APIs, and enterprise systems
Optimize pipeline performance, reliability, and scalability
Troubleshoot data ingestion, transformation, latency, accuracy, and integrity issues
Collaborate with Business Analysts, Data Scientists, Senior Data Engineers, and Architects
Support BI and analytics use cases, including dimensional modeling and aggregation optimization
Participate in CI/CD pipelines, DevOps workflows, and automated testing strategies
Contribute to metadata management and data cataloging
Provide Tier‑2 support for production data pipelines and datasets
Participate in peer code reviews and agile SCRUM ceremonies

Technology Stack
Azure Data Factory (ADF)
Azure Databricks (Spark / PySpark)
Azure Data Lake Storage (ADLS)
Azure Synapse Analytics
Azure SQL Databases / Data Warehouse
Python, Spark SQL, SQL
Microsoft Purview
Power BI
CI/CD & DevOps pipelines

Required Qualifications
Bachelor’s degree in Computer Science, Software Engineering,
Demonstrated experience as a Data Engineer building data pipelines
Hands‑on expertise with Azure Data Factory and Azure Databricks
Strong programming skills in Python, PySpark, Spark SQL, and SQL
Experience building data lakehouse and data warehouse pipelines
Strong understanding of data structures, data integration patterns, and processing frameworks
Knowledge of data governance, security, and data quality principles
Experience working in an Agile / SCRUM environment

📩 Interested?
Submit your résumé to: careers@cpus.ca