About this role
Role Name: Senior Data Engineer Location: Antwerp, Belgium Remote Work: Yes (Hybrid) Start Date: 25/08/2026 End Date: 15/07/2027 Language Requirement: Dutch at CEFR C2 level B. Main Responsibilities Data Pipeline Engineering Design, build, optimise, and maintain scalable data pipelines. Develop reliable data-processing workflows for large data volumes. Integrate data from multiple source systems. Build reusable and maintainable data-processing components. Monitor and improve pipeline performance and reliability. Microsoft Fabric Development Develop solutions using Microsoft Fabric. Work with Fabric pipelines, dataflows, and notebooks. Build and maintain modern analytics and data-processing workloads. Support scalable ingestion, transformation, and processing patterns. Optimise Fabric-based data solutions for performance and maintainability. Data Integration Integrate relational databases, APIs, files, applications, and other data sources. Design robust ingestion and transformation processes. Develop reusable data-integration patterns. Validate and monitor source-to-target data flows. Ensure reliable and consistent data delivery. Lakehouse & Data Warehouse Architecture Design and maintain cloud-based lakehouse and warehouse solutions. Implement medallion architecture using Bronze, Silver, and Gold layers. Support modern Azure-based data architectures. Contribute to domain-oriented and data-mesh concepts where applicable. Ensure scalability, maintainability, and reuse across data products. Data Modelling Translate reporting and analytics needs into data models. Develop reliable and reusable analytical datasets. Apply dimensional-modelling principles. Work with Kimball-based modelling concepts. Optimise data structures for reporting and business intelligence. Python & SQL Engineering Develop data-processing logic using Python. Use Python for ETL and data-engineering workloads. Develop and optimise SQL queries. Improve query performance. Support database-related analysis and troubleshooting. Reporting & Analytics Support Support Power BI and analytics environments. Prepare trusted datasets for reporting. Work with reporting specialists to understand analytical requirements. Improve the reliability and consistency of reporting data. Support self-service and enterprise analytics needs. Data Governance & Quality Contribute to data-governance standards. Implement data-quality controls. Support metadata and lineage practices. Identify and resolve data-quality issues. Promote consistent data-management practices across the platform. CI/CD & DataOps Support CI/CD for data solutions. Use version control for data engineering artefacts. Automate deployments across environments. Improve release and deployment processes. Apply modern DataOps and engineering practices. Documentation & Collaboration Document pipelines, dataflows, data models, and a C. Required Skills & Expertise Must Have Minimum 5 years of experience as a Data Engineer. Experience with cloud-based data architectures on Azure. Experience with lakehouse or data-warehouse concepts. Strong Microsoft Fabric experience, specifically: Pipelines Dataflows Notebooks Experience integrating data from multiple source systems. Experience supporting reporting and analytics environments. Minimum 3 years of Python experience within a data-engineering context. Experience with Python, Java, or Scala for data flows and ETL processes. Strong SQL knowledge. Query optimisation experience. Dutch language proficiency at CEFR C2 level. Should Have Experience within a public-sector, municipal, or complex enterprise environment. ETL design and implementation. CI/CD for data solutions. Version control. Automated deployment of data solutions. Database experience. Medallion architecture. Bronze, Silver, and Gold data layers. Power BI. Spark or Spark-based processing. Data governance. Data-quality management. Data lineage. Kimball dimensional modelling. Lakehouse architecture. Data Mesh. Domain-oriented data architecture.