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Level: Intermediate / Senior
Location: Belgium
Employment Type: Full-time
We are looking for a Data Engineer / ML Ops professional to design, build, and operate robust data pipelines and machine learning operations within a modern Data & Analytics ecosystem. The role combines strong data engineering foundations with ML Ops practices to support scalable, production-ready analytics and ML solutions.
Key ResponsibilitiesDesign, develop, and maintain data transformation pipelines using certified transformation tools
Implement and support ML Ops pipelines for model deployment, monitoring, and lifecycle management
Work with SAS DI Studio for data integration and transformation activities
Develop data processing and automation components using Python
Ensure data quality, reliability, performance, and scalability of data pipelines
Collaborate with data scientists, analysts, architects, and platform teams
Support CI/CD practices for data and ML workloads
Monitor and troubleshoot data pipelines and ML models in production
Contribute to platform modernization and continuous improvement initiatives
Intermediate to Senior experience in Data Engineering and/or ML Ops
Certification in a data transformation tool (mandatory)
Hands-on knowledge of SAS DI Studio
Strong programming skills in Python
Solid understanding of data modeling, ETL/ELT, and pipeline orchestration
Experience with ML lifecycle management (deployment, monitoring, versioning)
At least one of the following languages:
Dutch (NL)
French (FR)
English (EN)
Professional working proficiency in the selected language
Experience with cloud-based data platforms
Familiarity with containerization and orchestration (Docker, Kubernetes)
Experience in regulated environments (banking, insurance, public sector)
Knowledge of DevOps or DataOps practices
Work on modern data and ML platforms with real business impact
Opportunity to combine data engineering and ML Ops in a mature D&A environment
Flexible, multilingual Belgian work context
Key Skills
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