We are partnering with a client launching a large-scale data platform modernisation initiative to migrate a legacy SAS-based ETL ecosystem to Python. Following a highly successful Proof of Concept (POC), the team proved that Generative AI can drastically accelerate migration by automating code translation, functional analysis, and documentation.
We are looking for a Python Data Engineer to help scale and industrialise this AI-powered migration framework, moving the initial pipelines into a fully production-ready, enterprise-grade environment.
Position Overview
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Focus: SAS to Python Migration & ETL Modernisation
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Location: Belgium
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Environment: Agile, cross-functional team including Data Architects, AI Architects, and SAS Experts
Key Responsibilities
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ETL Development: Design, develop, and maintain clean, reusable Python-based ETL pipelines.
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AI-Assisted Migration: Leverage Generative AI coding assistants (such as GitHub Copilot and Claude) to accelerate development, automate repetitive translation tasks, and improve code quality.
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Functional Analysis: Analyse existing legacy SAS code to ensure strict functional equivalence and zero data loss in the new Python implementations.
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Pipeline Industrialisation: Contribute to building and scaling a robust, automated AI-assisted migration pipeline that can handle complex legacy data structures.
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Quality & Best Practices: Participate in code reviews, automated testing, and validation cycles between business and technical experts, while supporting the broader team’s adoption of Python development best practices.
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Innovation: Produce technical documentation with the support of AI tools and participate in internal hackathons and workshops exploring the future of software engineering.
Technical Stack
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Core Languages: Python, SAS (specifically for reading, interpreting, and reverse-engineering logic)
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AI & Engineering Tools: GitHub Copilot, Claude, Agentic AI frameworks
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Version Control & CI/CD: Git, GitHub, modern CI/CD automation practices
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Data Domain: ETL Pipelines, Data Platform Modernisation, Automated Testing
Candidate Requirements
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Python Expertise: Strong, hands-on experience in Python development and data engineering.
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Data Background: Solid background in building and maintaining ETL pipelines and working with large-scale data environments.
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Collaboration Tools: Proficient with Git and collaborative, agile software development workflows.
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AI Focus: A strong interest in Generative AI, prompt engineering for code generation, and AI-powered software development.
Nice to Have
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SAS Familiarity: Previous experience with or exposure to SAS code, allowing you to easily map business rules from legacy systems.
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System Modernisation: Experience working on legacy-to-cloud migrations or major application modernisation programs.
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Framework Design: Experience building reusable software components or internal developer frameworks.
