Job Title: Data Engineer / ML Ops

Level: Intermediate / Senior
Location: Belgium
Employment Type: Full-time

Role Overview

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 Responsibilities

• Design, 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

Required Experience & Skills

• 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)

Language Requirements

• At least one of the following languages:

  • Dutch (NL)

  • French (FR)

  • English (EN)

• Professional working proficiency in the selected language

Nice to Have

• 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

Why Join

• 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