> Markdown version of [/jobs/ext/2205059-data-engineer-genai](https://www.wearedevelopers.com/jobs/ext/2205059-data-engineer-genai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - GenAI - **Company:** Artefact - **Location:** Oudergem, Belgium - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Big Data, Computer Programming, Data Architecture, Data Cleansing, Information Engineering, Data Governance, Data Transformation, Python (Programming Language), Machine Learning, Rapid Prototyping Process, Software Engineering, SQL Databases, Unstructured Data, Feature Engineering, Retrieval-Augmented Generation, Large Language Models, Apache Spark, Generative AI, Git, Containerization, Pyspark, Kubernetes, Information Technology, Data Management, Data Pipelines, Docker, Databricks, Microservices - **Published:** August 24, 2026 - **Apply:** https://www.adzuna.be/details/5853683482 ## About the Role * Experienced Professional: At least 3-5 years of industry experience in data engineering, ideally within a consulting environment, with exposure to data preparation for AI/ML. * Deep Technical Skillset: Strong programming skills in Python and proven expertise in Spark (PySpark, SparkSQL) for large-scale data processing and feature engineering. * Data Transformation Expert: Extensive experience with dbt for data modeling, and a strong curiosity about emerging patterns in "LLMOps" and vector data management. * Consulting Mindset: Proven ability to navigate multidisciplinary environments and communicate how high-quality data architecture is the primary bottleneck for successful GenAI deployment. * Education: A Master's in a quantitative field (Computer Science, Engineering, Mathematics, or a related field). * Linguistic Versatility: Proficiency in English is required; fluency in Dutch or French is a major advantage for our Belgian market. ## Description As a Data Engineer in our GenAI practice, you will own the end-to-end execution of complex technical challenges. You won't just "move" data; you will build the specialized infrastructure and data flywheels that power the next generation of Generative AI, RAG systems, and autonomous agents. * Deploy GenAI-Ready Production Pipelines: Design and deploy advanced data pipelines both batch and streaming optimized for processing unstructured data (text, images, audio) to fuel LLM fine-tuning and retrieval-augmented generation. * Build Scalable AI Platforms & Vector DBs: Hands-on development using modern cloud platforms like Databricks, Azure, or AWS. * Establish Engineering Excellence for LLMs: Implement best practices in data transformation (dbt), orchestration (Airflow, Prefect, or Dagster), and data governance to ensure that AI solutions are reliable, safe, and compliant at enterprise scale. * Collaborate on AI Innovation: Work closely with Machine Learning Engineers and Generative AI Specialists to design data models and "data-as-a-service" layers that enable rapid prototyping and scaling of AI agents. * Software Engineering Foundation: Advocate for clean, maintainable code using Python, SQL, and Git, and leverage containerization (Docker/Kubernetes) to deploy AI-driven microservices. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)