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# Data Engineer JP055033

- **Company:** ITProposal
- **Location:** Namen, Belgium
- **Contract:** Temporary contract
- **Skills:** Data Analysis, Databases, Data Validation, Data Cleansing, Data Control, Data Deduplication, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Reference Data, Talend
- **Published:** August 13, 2026
- **Apply:** https://www.adzuna.be/details/5839875419

## About the Role

* Confirmed experience as a Data Engineer / ETL-ELT Engineer.
 * Strong practical experience with ETL tools, particularly FME; knowledge of Talend is also relevant.
 * Strong knowledge of Data Quality Management.
 * Experience with data integration, transformation, normalisation and consolidation.
 * Experience analysing and designing database management systems.
 * Understanding of data governance principles, including DAMA concepts.
 * Experience with data validation, anomaly detection and data cleansing.
 * Strong analytical and problem-solving skills., Experience in the public sector is an advantage. Candidates may also be asked to describe their relevant experience in project management, data modelling/conceptualisation and data quality control. The selection is weighted 70% on technical skills and 30% on a proposed methodology note of maximum one page.
If you have strong experience in Data Engineering, FME, ETL/ELT, Data Integration and Data Quality Management, we would like to hear from you.

## Description

* Design and implement data integration, data quality and data monitoring processes.
 * Build and maintain ETL/data integration pipelines, primarily using FME.
 * Define transformation, normalisation and consolidation rules for data coming from multiple sources.
 * Develop connectors and integration flows for feeding and distributing reference data.
 * Implement automated data quality controls, including:
 + Format validation
 + Completeness checks
 + Temporal consistency checks
 + Cross-source validation
 + Uniqueness controls
 * Design mechanisms for detecting anomalies and inconsistencies, including duplicates, outliers and conflicts between systems or data sources.
 * Develop automated data cleansing and remediation processes, including standardisation, normalisation, deduplication and data enrichment.
 * Define and monitor key data quality indicators such as accuracy, completeness, consistency, uniqueness, freshness and compliance.
 * Contribute to dashboards, reporting and continuous improvement of data quality.
 * Support technical teams in resolving data-related incidents and contribute to integration and testing activities.


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