The SPW Companies Reference Database is part of the drive to evolve the administration towards a more user-oriented and data-oriented approach. It addresses the current situation, characterized by the dispersion, duplication, and heterogeneity of company data across numerous business applications. This fragmentation undermines data quality, their reuse, the consistency of administrative processes, and the SPW's cross-functional analysis capability. The reference database thus aims to establish a common reference source, gradually fed by federal and Walloon sources, in order to consolidate company identification, reduce administrative burden, improve data quality, and support the “Only Once” principle.

The Companies Reference Database is the single source for company identification within the Service Public de Wallonie. Its integration into the SPW’s application and data environment will be progressive, according to an established roll-out timeline.

By groups, the various data sources managing information related to companies will be connected to the reference database. This connection will be bi-directional:

• Feeding the reference database: identifier, data related to the processes identified and required by the reference database
• Feeding by the reference database: BCE identifier + SPW identifier, identification data, characterization, activity typology, representatives..., additional data (BCE, files identified from other sources...)

In this context, the Data Engineer will be responsible for defining the integration, quality control, detection, and monitoring processes for inconsistencies in the companies reference database.

• Design, in collaboration with all SPW Digital teams,
• Of the feeding and quality control processes for the reference database
• Of inconsistency tracking and data cleansing mechanisms

• Of process monitoring

• Implementation of these processes, testing, rollout

They will join a team including a project manager, a technical coordinator, and an analyst. The team will be part of the Data Management and Valorization Directorate (DGVD).

Context

The SPW Companies Reference Database is part of the drive to evolve the administration towards a more user-oriented and data-oriented approach. It addresses the current situation, characterized by the dispersion, duplication, and heterogeneity of company data across numerous business applications. This fragmentation undermines data quality, their reuse, the consistency of administrative processes, and the SPW's cross-functional analysis capability. The reference database thus aims to establish a common reference source, gradually fed by federal and Walloon sources, in order to consolidate company identification, reduce administrative burden, improve data quality, and support the “Only Once” principle.

The Companies Reference Database is the single source for company identification within the Service Public de Wallonie. Its integration into the SPW’s application and data environment will be progressive, according to an established roll-out timeline.

By groups, the various data sources managing information related to companies will be connected to the reference database. This connection will be bi-directional:

In this context, the Data Engineer will be responsible for defining the integration, quality control, detection, and monitoring processes for inconsistencies in the companies reference database.

They will join a team including a project manager, a technical coordinator, and an analyst. The team will be part of the Data Management and Valorization Directorate (DGVD).

Definitions and Reference Elements

Main Objectives

The SPW Companies Reference Database aims to become the cross-functional reference source for the identification and knowledge of companies, by consolidating data scattered across applications, improving their quality, harmonizing definitions, reducing redundancies, and enabling controlled reuse of data for the benefit of business units, users, and public management.

Tasks and Activities

Define the integration, analysis, and quality control processes, detection and monitoring of inconsistencies, and data cleansing for the companies reference database. The Data Engineer is responsible for the design, implementation, and continuous improvement of processes to feed, control, secure, and maintain the quality of data in the Companies Reference Database. They ensure consistent integration of data from multiple internal and external sources, implement anomaly detection mechanisms, and guarantee the availability of reliable, complete, and reusable data for all SPW applications and processes.

This mission is based on a “quality by design” approach, where data quality is integrated from the ingestion, integration, and exploitation stages of the reference database. In this context, they will notably perform the following tasks:

The Data Engineer brings their expertise to define, design, and implement.

They collaborate with the Data Virtualization Service Center and the DGVD to ensure the consistency of the consolidated view of companies made available to applications.

The Data Engineer brings their expertise to:

In liaison with the Data Management and Valorization Directorate team, they define the quality controls applicable to data upon integration into the reference database. To do this, they rely on FME tools as well as DataLift developed within the Data Management and Valorization Directorate.

They ensure in particular to define the preliminary quality controls for the integration of data into the reference database in terms of:

They ensure the automation of these controls during ingestion and on data already present in the reference database, and to provide future tools allowing the future manager of the companies reference database to evolve the validation rules according to new business needs and regulatory developments.

The Data Engineer brings their expertise to:

• Develop automated data cleansing processes:
• Design mechanisms and processes enabling
• Implement a permanent data quality monitoring system.
• Measure key quality indicators:
• Analyze trends and propose technical or organizational improvements.

During the construction phase and the progressive connection of the reference database to SPW data sources, the Data Engineer.

The Data Engineer brings their expertise to.

Deliverables

See above.

Soft Skills

• Dynamic and flexible person.
• Good communication and assertiveness.
• Pragmatic approach to problems and solutions.
• Excellent command of French, strong oral and written communication skills, active listening.
• Service and customer-oriented, able to understand and respond to the urgencies and needs of data managers.

Evaluation Method

The quality of the offer will be evaluated according to a grid of weighted criteria structured as follows:

• 70% – Technical skills (data modeling and quality control) – based on the CV
• 30% – Proposed working methodology (understanding of context, tools, and legal issues) – based on a note (maximum 1 page) accompanying the CV

Each sub-criterion will be scored on a scale of 1 to 5, with weighting applied according to its importance. The final score of the offer will result from the weighted average of the criteria, allowing for an objective comparison between candidates.

Candidates may be invited to an interview before a jury whose composition will be communicated later.

The interview may take place remotely if circumstances require.