Key Responsibilities

• Design, build, and maintain scalable, efficient, and robust ETL pipelines for AI and Machine Learning workflows.
• Ensure optimal storage strategies to support Machine Learning models and analyses.
• Monitor and guarantee the quality, consistency, and integrity of data across systems and sources.
• Collaborate with data scientists, Machine Learning engineers, and analysts to understand data requirements and deliver tailored solutions.
• Optimize data workflows for performance, scalability, and cost-effectiveness in cloud or on-premises environments.
• Stay up to date with developments in AI, Machine Learning, and Big Data technologies to contribute to innovative solutions.
• Work with Machine Learning engineers to deploy AI models and ensure seamless integration into production systems.
• Implement mechanisms to monitor and retrain models by providing real-time data input.

Candidate Profile

• University degree in quantitative fields such as Statistics, Mathematics, Computer Science, or a related discipline.
•  A master’s degree in data science, AI/ML, or a relevant technical field is preferred.
• At least 3 years of experience in data engineering or related roles.
• Familiar with tools such as Python, Spark, Azure (Data Lake, Synapse), SQL, NoSQL, Kafka, Docker, Terraform, and similar technologies.
• Strong problem-solving skills and creative thinking.
• Excellent communication skills, able to present complex data clearly and concisely.
• Fluent in Dutch, French, and English.
• Able to work independently and collaboratively, manage multiple priorities, and meet tight deadlines.