Databricks Data Engineer

Role: Databricks Data Engineer
Location: Downtown Toronto, ON
Length: Expected 6 month contract

Our client is an industry leading firm that serves clients on a variety of specialized projects that help them to work smarter, grow faster and compete better.

Why join our contract workforce?

– Interesting work: Deliver work that matters to you. We provide the opportunity to get involved in highly technical, complex and interesting projects where you can leverage your specific skillset and expertise to add value.
– Enrich your skills: Access to best-in-class technology, market intelligence and resources to advance your unique technical skills and expertise. Work alongside diverse, passionate and highly skilled professionals working together to drive innovation.
– Flexible opportunities: Find projects that match when and where you want to work.

The opportunity
This engagement is a Databricks Implementation Project focused on building a robust, scalable data platform on AWS using Databricks, Apache Spark, and Delta Lake. The project aims to establish modern data engineering practices, accelerate reliable data product delivery, and enable high-quality analytics and operational reporting. Work will include end-to-end pipeline development, data modeling, automated quality controls, operational monitoring, and performance optimization in a hybrid environment. 

• Design, develop, and maintain data pipelines and data products in Databricks on AWS using Apache Spark and Delta Lake.
• Implement ingestion, transformation, and data curation patterns aligned with architectural standards and business requirements.
• Build and maintain curated datasets and data models that are reliable, testable, and well-documented.
• Ensure data quality through automated controls, validation checks, and transparent exception handling.
• Implement monitoring, logging, and alerting to support predictable and stable operations.
• Optimize workloads for performance and cost through efficient Spark design and cluster configuration.
• Leverage automation and intelligent code-assistance tools to programmatically generate and evolve data models, transformation logic, and pipeline components with strong validation and review practices.
• Participate in production support, incident analyses, and continuous improvement activities.

Your qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Typically, 3-6 years of experience delivering production-grade data engineering solutions.
• Strong hands-on experience with Databricks and Apache Spark, with Py Spark preferred.
• Proficiency in SQL with an understanding of performance, data correctness, and maintainability.
• Solid knowledge of Delta Lake concepts including transactional reliability and schema evolution.
• Practical experience with AWS fundamentals relevant to data platforms, including S3 and IAM.
• Experience working with automated testing, CI/CD pipelines, and version-controlled deployments.
• Experience using intelligent code-assistance tools (e.g., GitBHub Copilot, OpenAI, Databricks Assistant) to accelerate data model and pipeline development, with appropriate validation and review.
• Strong analytical skills, sound engineering judgment, and the ability to work effectively across teams.
• Proficiency in English at a B2/C1 level.