A public administration in Belgium is building a shared enterprise registry for company data to replace fragmented, duplicated and inconsistent records held across business applications. As a medior Data Engineer, you will design data integration and data quality management processes using FME ETL pipelines and DataLift, connecting federal and Walloon sources to one reference for enterprise identification.
The mission
The registry is intended to become the common source for identifying enterprises across the administration, replacing fragmented records held in many business applications. It will receive identifiers and selected process data from contributing systems, then distribute consolidated enterprise identifiers, including BCE and internal registry identifiers, identity details, activity classifications, representatives and other source data back to those systems. The rollout will progressively connect sources from Wallonia and federal sources through bidirectional exchanges. This supports data reuse, more consistent administrative processes and the Only Once principle.
You will join a project team comprising a project manager, technical coordinator and analyst within the data management and valorisation directorate. Your scope covers the design, implementation and testing of ETL, validation, anomaly tracking, data cleansing and monitoring processes. You will work with digital delivery teams and the data virtualisation service to assess each application connection and maintain a coherent consolidated view. The role also includes documentation, incident support and continuous improvement so operational teams can maintain the registry after rollout.
Your responsibilities
- Build FME ETL pipelines for enterprise data, implementing connectors, transformations, normalisation and traceable bidirectional data flows.
- Define automated data quality validation with FME and DataLift, covering formats, completeness, temporal consistency, cross-source validation and uniqueness.
- Implement reference-data consolidation mechanisms for unique identifiers, deduplication, source prioritisation and conflict management.
- Detect and remediate duplicates, outliers and inconsistencies through standardisation, enrichment, correction and root-cause analysis.
- Establish monitoring dashboards, quality indicators and reports covering accuracy, completeness, consistency, uniqueness, freshness and compliance.
- Coordinate application onboarding by analysing technical impacts, supporting integration tests, resolving data incidents and documenting operational processes.
Your profile
Essential skills
- Apply data governance principles, including DAMA-based approaches, to reference data and enterprise information.
- Use ETL tools in practice, with experience in FME and Talend and the ability to follow public-sector integration standards.
- Design and analyse database management systems, translating functional requirements into coherent data models and processes.
- Implement Data Quality Management practices across ingestion, integration and ongoing data use.
- Investigate data defects pragmatically, classify anomalies by criticality and propose corrective actions at the appropriate source.
- Communicate clearly and assertively with project, technical and data management stakeholders while maintaining a service-oriented approach.
Languages
- French, C1 or higher, with strong written and spoken communication skills.