Shape data pipelines as a Big Data Engineer focused on analytics. Utilize your PySpark expertise on Databricks to enhance data processing and support advanced workflow needs.
This position involves designing and maintaining high-performance data pipelines while enabling feature engineering and model support. You'll collaborate with data scientists to refine data requirements and optimize for performance in cloud environments. Successful applicants will bring robust experience in data engineering, particularly with large datasets and analytical models.
Key Responsibilities:
• Build scalable data pipelines using PySpark
• Transform source data for analytics and models
• Optimize Spark jobs for performance and efficiency
• Implement data quality checks and validation
• Collaborate on feature engineering and model iteration
Requirements:
• Degree in data engineering or related field
• Robust experience with large datasets and data engineering
• Proficiency in PySpark and Python coding
• Experience designing data pipelines for analytics
• Ability to communicate technical concepts effectively
Leverage your data skills to drive impactful analytics solutions and support innovative projects in a collaborative environment.
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Apply on Kit Job: kitjob.ca/job/2fsild
📌 Innovative Big Data Engineer for Scalable Analytics Solutions (Toronto)
🏢 Canadian Tire Financial Services
📍 Toronto
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