This role focuses on developing and enhancing custom software solutions. You will design, code, and improve components within various systems and applications, leveraging modern frameworks and agile methodologies to deliver scalable, high-performing results.

Your primary objective will be to create tailored solutions that address specific business requirements. This involves a collaborative approach to ensure the final product is efficient and effective.

Lead the migration of legacy SAS data preparation jobs to a modern Python-based data engineering framework. Analyze existing SAS scripts and workflows to understand logic and dependencies. Re-engineer SAS jobs into scalable, efficient Python data pipelines. Collaborate with analysts, scientists, and engineers to validate converted workflows. Optimize the performance of new Python workflows and ensure data quality. Document migration processes, coding standards, and pipeline configurations. Integrate new pipelines with Google Cloud Platform. Provide support for testing, validation, and production deployment.

A minimum of 3 years of experience in Python programming is essential. Proficiency in Python, including Pandas and Data Frames, is required. Strong knowledge of GCP, database systems, and ETL best practices is necessary. Experience with SQL on the GCP platform is also important. Familiarity with modern Python development frameworks and libraries is expected. Version control system experience, particularly Git, is required. 15 years of full-time education is a prerequisite for this role.