Data Engineer - GenAI
Quick Summary
Design and deploy advanced data pipelines both batch and streaming optimized for processing unstructured data (text, images, audio) to fuel LLM fine-tu
Are you an experienced Data Engineer with a passion for building high-performance data pipelines and scalable cloud architectures for the Generative AI era? Artefact Belgium is looking for a Data Engineer to drive innovation and deliver robust data foundations for our global clients. If you have a solid track record in data engineering and consulting, we invite you to shape the future of AI-driven solutions with us in Brussels.
Founded in Paris, Artefact is a next-generation consulting firm specializing in data, analytics, and AI, focused on transforming data into business impact. We help clients grow their data and digital capabilities while growing ourselves. Our engineering team in Belgium works on the most advanced applications of data technology, from large-scale data platforms to supporting state-of-the-art GenAI projects. Our inclusive and forward-thinking culture encourages creativity, collaboration, and professional growth.
Responsibilities
~1 min readAs 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.
- 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.
What We Offer
~1 min readListing Details
- Posted
- March 1, 2026
- First seen
- March 26, 2026
- Last seen
- April 13, 2026
Posting Health
- Days active
- 18
- Repost count
- 0
- Trust Level
- 39%
- Scored at
- April 13, 2026
Signal breakdown
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