Data Engineer Python & AI

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.

• Focus: SAS to Python Migration & ETL Modernisation
• Location: Belgium
• Environment: Agile, cross-functional team including Data Architects, AI Architects, and SAS Experts

• ETL Development: Design, develop, and maintain clean, reusable Python-based ETL pipelines.
• 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.
• Functional Analysis: Analyse existing legacy SAS code to ensure strict functional equivalence and zero data loss in the new Python implementations.
• Pipeline Industrialisation: Contribute to building and scaling a robust, automated AI-assisted migration pipeline that can handle complex legacy data structures.
• 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.
• Innovation: Produce technical documentation with the support of AI tools and participate in internal hackathons and workshops exploring the future of software engineering.

• Core Languages: Python, SAS (specifically for reading, interpreting, and reverse-engineering logic)
• AI & Engineering Tools: GitHub Copilot, Claude, Agentic AI frameworks
• Version Control & CI/CD: Git, GitHub, modern CI/CD automation practices
• Data Domain: ETL Pipelines, Data Platform Modernisation, Automated Testing

• Python Expertise: Strong, hands-on experience in Python development and data engineering.
• Data Background: Solid background in building and maintaining ETL pipelines and working with large-scale data environments.
• Collaboration Tools: Proficient with Git and collaborative, agile software development workflows.
• AI Focus: A strong interest in Generative AI, prompt engineering for code generation, and AI-powered software development.

• SAS Familiarity: Previous experience with or exposure to SAS code, allowing you to easily map business rules from legacy systems.
• System Modernisation: Experience working on legacy-to-cloud migrations or major application modernisation programs.
• Framework Design: Experience building reusable software components or internal developer frameworks.