Opportunity Description
Join the technology transformation team in Toronto as a Data Engineer, focusing on migrating SAS processes to Python and PySpark. Drive data pipeline optimization in HDFS/Hive and AWS S3 environments.
This role is vital for improving credit risk management through high-performance data pipelines. You’ll play a hands-on role in translating complex data needs into actionable insights while adhering to best coding practices. Collaborate closely with data scientists and stakeholders to architect scalable solutions that support analytical needs.
Key Responsibilities:
• Build and optimize data pipelines using Python and PySpark
• Lead initiatives to migrate SAS processes to cloud-ready solutions
• Architect data workflows for credit risk analytics
• Write production-quality code with testing and documentation
• Collaborate via GitHub for code quality and reviews
Requirements:
• 3+ years of data engineering experience<...
This role is vital for improving credit risk management through high-performance data pipelines. You’ll play a hands-on role in translating complex data needs into actionable insights while adhering to best coding practices. Collaborate closely with data scientists and stakeholders to architect scalable solutions that support analytical needs.
Key Responsibilities:
• Build and optimize data pipelines using Python and PySpark
• Lead initiatives to migrate SAS processes to cloud-ready solutions
• Architect data workflows for credit risk analytics
• Write production-quality code with testing and documentation
• Collaborate via GitHub for code quality and reviews
Requirements:
• 3+ years of data engineering experience<...
Interested in this opportunity? Apply now through Expertini.
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