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Senior PySpark Developer to support the design, development, and maintenance of modernized data pipelines for a large-scale data modernization initiative

4 weeks ago


Toronto, Canada S.i. Systèmes Full time

Our valued public sector client is seeking Senior PySpark Developer to support the design, development, and maintenance of modernized data pipelines for a large-scale data modernization initiative Initial 5-month contract (until March 31, 2026) with a strong possibility of extension. Remote work arrangement within Canada, full-time, Monday to Friday. The successful candidates will be responsible for developing, testing, and supporting data ingestion and transformation pipelines using PySpark, Python, and AWS-based technologies, following Agile development practices and CI/CD principles. The developers will work closely with technical and business teams to deliver scalable, high-performance data solutions that support enterprise analytics and reporting. ResponsibilitiesDesign, develop, and maintain large-scale data processing pipelines using PySpark, Spark SQL, and Python.Collaborate with business and technical stakeholders to translate business requirements into technical solutions.Develop modular, reusable, and maintainable code following software development best practices.Implement automated testing frameworks to ensure data quality and reliability.Participate in peer code reviews and apply CI/CD practices using Git-based workflows.Work with Airflow or equivalent orchestration tools for pipeline scheduling and automation.Develop and maintain ETL mappings, documentation, and data flow diagrams.Deploy and monitor data workflows in a cloud-based environment (AWS EMR, Redshift, S3, Lambda).Troubleshoot performance issues and optimize Spark jobs for scalability and efficiency.Ensure compliance with quality assurance and change management procedures. Must-Have5+ years of hands-on programming experience in Python and SQL, writing modular, maintainable code.3+ years of strong experience developing PySpark data pipelines for large-scale data processing.Solid understanding of Spark DataFrames, Spark SQL, and distributed data processing concepts.Practical experience working in AWS Cloud environments (e.g., EMR, Redshift, Lambda).Strong knowledge of MySQL or equivalent relational databases.Proficiency with Git, unit testing, and release automation.Familiarity with Apache Iceberg or similar open table formats.Experience with Airflow or equivalent orchestration frameworks.Excellent problem-solving and troubleshooting skills, with a proactive, collaborative attitude.Strong oral and written communication skills in English. Nice to HaveExperience with AWS Cloud Development Kit (CDK) for Python.Familiarity with serverless architecture (AWS Lambda, event-driven design).Exposure to DevOps automation and continuous integration pipelines.Previous experience working on healthcare or public sector data platforms. Apply