Data Engineer - GenAI
Role details
Job location
Tech stack
Job 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.
Requirements
Do you have experience in Spark?, Do you have a Master's degree?, * 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.
Benefits & conditions
- Competitive Compensation: An attractive package aligned with your expertise, including a mobility budget or company car and premium insurance.
- High-Impact Opportunities: Work with state-of-the-art technologies on global projects that transform the world's leading brands through Generative AI.
- Professional Growth: Access to a substantial training budget for individual learning, research into new AI frameworks, and certifications.
- A Collaborative Workplace: Join a diverse team where fun and professional excellence go hand-in-hand, with access to 2,000+ colleagues across 34 global offices.
This position is based in Brussels, At Artefact Belgium, we value expertise, curiosity, and a drive to innovate. If you're ready to build the data engines of the AI future, we'd love to hear from you.