Data Engineer Python & AI

Over deze functie

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

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

Key Responsibilities

* **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.

Technical Stack

* **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