Data Consultant

• Data pipelines & integration:
• Design, build and maintain data ingestion and transformation pipelines from various sources (files, APIs, databases, SaaS systems, …).
• Implement robust ETL/ELT processes using modern data engineering tools and frameworks.
• Ensure data is delivered in a reliable, performant and secure way.
• Data modeling & serving:
• Design and implement data models for analytics and reporting (e.g. data warehouses, data marts, curated datasets).
• Prepare and expose data to BI and analytics tools and to data science / ML use cases.
• Apply good practices for documentation, naming conventions and reusability.
• Data platforms & environments:
• Work with modern data platforms and environments, on-premise or in the cloud, depending on the client context.
• Contribute to the design and implementation of the different layers of a data platform (ingestion, storage, processing, serving).
• Help ensure that solutions are scalable, maintainable and aligned with the client’s architecture and standards.
• Quality, reliability & operations:
• Implement data quality checks, monitoring and logging to ensure trustworthy data.
• Troubleshoot and optimize pipelines and queries for performance and cost-efficiency.
• Use version control and automation practices to industrialize and secure deployments.
• Collaboration with stakeholders:
• Work closely with data architects, BI developers, analysts, data scientists and business stakeholders to understand requirements and translate them into technical solutions.
• Communicate clearly on progress, risks and technical decisions, and contribute to a constructive team dynamic.

• At least 3–5 years of experience as a Data Engineer or in a similar role, ideally in a consulting / project-based environment.
• Strong skills in SQL and a good understanding of data modeling for analytics (data warehouse concepts, dimensional modeling / star schema, …).
• Experience building data pipelines and data solutions with one or more modern tools / technologies (e.g. scripting or programming languages, integration tools, databases, BI or analytics platforms).
• Good programming skills in Python (or another language commonly used for data engineering).
• Familiarity with version control (Git or similar) and basic automation / CI/CD practices.
• Comfortable working directly with business and IT stakeholders, with good communication skills.
• Used to working as a freelancer: autonomous, professional, able to integrate quickly into new teams and environments.
• Fluent in French or Dutch, and comfortable in English (spoken and written).

Nice to have.

• Experience in industries such as banking, insurance, energy, e-commerce, public sector.
• Exposure to modern concepts such as data platforms, data lakes, Lakehouse, data mesh, data products.
• Experience with tenders, RFPs or long-term managed services is a plus.