Databricks Engineer

Skills

Job Specifications

Job Title: Databricks Engineer

Location: Toronto, Canada (Hybrid)

Job Type: Full-time (Contract)

Key Responsibilities:

• Design, develop, and maintain scalable and efficient data pipelines using Databricks, PySpark, Delta Lake, and Azure technologies.

• Build new data workflows and enhance existing pipelines to improve performance, scalability, and reliability.

• Architect and implement ETL processes aligned with data governance and quality standards.

• Develop data models and optimize SQL scripts for large datasets.

• Collaborate closely with cross-functional teams in an agile environment to deliver production-ready solutions.

• Troubleshoot and resolve complex data issues, including performance bottlenecks and workflow failures.

• Participate in architecture, design reviews, and technical discussions to guide data engineering best practices.

• Work with Azure components such as ADLS, ADF, Synapse, and integrate data from SQL-based sources including MySQL.

Required Skills & Qualifications:

• 3–8 years of hands-on data engineering experience with a strong focus on Azure Databricks.

• Strong proficiency in PySpark, SQL, Delta Lake, and pipeline optimization.

• Solid understanding of ETL design principles, data modeling, and data governance frameworks.

• Experience working with Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), and enterprise-level data systems.

• Experience integrating and transforming data from SQL sources, especially MySQL.

• Strong analytical, troubleshooting, and debugging skills in large-scale data environments.

• Excellent communication skills with the ability to articulate complex technical concepts.

• Ability to work independently and collaboratively within an agile team structure.

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