Data Analyst

For one of our clients in Namur, Belgium, we are looking for an experienced Data Analyst for a long-term freelance assignment.

Language: French – excellent written and spoken level required

Contract: Freelance

Context

Our client is strengthening the use, sharing and governance of data across its organisation. The structured, secure and documented sharing of data has become a strategic priority.

A dedicated data-sharing platform is used to facilitate the distribution of both geographic and non-geographic data, while ensuring data quality, compliance, documentation and long-term sustainability.

The Data Analyst is involved throughout the entire data lifecycle, from analysing business requirements to data publication, documentation, quality monitoring and maintenance.

The role also contributes to application development projects at an early stage by applying data-centric principles to ensure that data is properly structured, reusable, interoperable and ready for future sharing.

The Data Analyst must be able to analyse datasets, assess their maturity and ensure compliance with applicable standards, regulations and internal data governance rules.

The position combines technical, analytical and communication skills. Strong understanding of business requirements and the ability to communicate with Data Owners, Data Managers, technical teams and end users are essential.

Main Objectives

• Ensure legal and technical compliance with requirements such as INSPIRE, High-Value Datasets (HVD), Open Data and internal data standards.
• Guarantee data quality, reliability and traceability through appropriate validation and monitoring mechanisms.
• Industrialise and automate data sharing by transforming production data (vPROD) into usable and regularly updated distribution data (vDIFF) using FME and/or Denodo.
• Improve data accessibility and discoverability through high-quality metadata and appropriate publication channels such as geoportals, APIs, web services and GIS platforms.
• Strengthen data governance by clearly defining responsibilities between data producers, Data Owners and Data Managers.

Key Concepts

Data Committee: A governance group responsible for coordinating and prioritising data-sharing activities.

Data-sharing platform: A solution used for reading source data, documentation, modelling, quality control and transformation.

Data Owner: The business authority responsible for a dataset, including its business rules, access conditions, quality, compliance and security requirements.

Data Manager: The entity responsible for the operational management of data, including production, quality, integrity, storage, updates, documentation and distribution.

vPROD: The source version of a dataset produced and maintained by the Data Manager.

vDIFF: The transformed distribution version made available to the target audience.

Metadata platform: The organisation's solution for managing and maintaining dataset metadata.

Responsibilities

1. Data Request Assessment

• Analyse incoming data-sharing requests and application-related data requirements.
• Assess relevance, priorities and applicable European or legal requirements.
• Assign datasets to Data Analysts.

2. Contact with Data Managers

• Inform the Data Manager that the dataset is being prepared for sharing.
• Explain the overall process, requirements and support available.

3. Project Planning

Prepare a project plan covering:

• Target users
• Objectives of data sharing
• Source data and access points
• Update frequency
• Access and usage conditions
• Open Data or other licensing requirements
• Stakeholders
• Target platforms and publication channels

4. Metadata

• Create and maintain the dataset metadata in collaboration with the metadata team and Data Manager.
• Ensure metadata is complete, accurate and up to date.

5. Source Data Analysis

Analyse the vPROD dataset, including:

• Structure
• Content
• Data maturity
• Quality issues
• Potential compliance issues

If the dataset is not sufficiently mature for publication, coordinate with the relevant data governance stakeholders and guide the Data Manager towards the appropriate support teams.

Design and document the vDIFF distribution model, including:

• Tables and attributes
• Names and aliases
• Descriptions
• Value lists
• Constraints
• Access conditions
• Technical specifications

Ensure the resulting model supports interopera