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# Data & AI consultant

- **Company:** Pauwels Consulting
- **Location:** Zaventem, Belgium
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Microsoft Azure, Information Engineering, Extract Transform Load (ETL), Data Systems, Document-Oriented Databases, Python (Programming Language), Machine Learning, SQL Azure, Power BI, Tensorflow, SQL Databases, Azure Data Factory, Large Language Models, Data Lakes, Scikit Learn, Machine Learning Operations, Data Pipelines, Databricks
- **Published:** August 7, 2026
- **Apply:** https://www.jobinhoreca.com/job/viewjob/3072601/data-ai-consultant.html

## About the Role

* Analytics & BI: Solid experience with Power BI (or equivalent) and the ability to tell a clear story with data.
 * Databricks: Hands-on experience with notebooks, pipelines, and Unity Catalog.
 * Data Engineering: Comfortable writing clean Python or SQL to transform and model data.
 * Azure Data Services: Familiarity with Azure Data Factory, Azure SQL, Data Lake Storage or equivalent.
 * Curious mindset with an appetite for self-development.
 * Working proficiency in English & Dutch.

Nice-to-haves

 * Experience with ML frameworks (scikit-learn, MLflow, etc.) or LLM tooling.
 * Relevant Azure or Databricks certifications.
 * Experience in a consulting or client-facing environment.

## Description

* Data Analytics & Reporting: Design and deliver dashboards and reports in Power BI that give clients clear, actionable insight.
 * Databricks Engineering: Build and maintain ETL/ELT pipelines following the medallion architecture, from raw ingestion to curated, analytics-ready datasets.
 * AI & ML Use Cases: Collaborate with clients to scope, develop and deploy AI/ML models, including LLMs, that solve real business problems.
 * Data Modelling: Structure and document data models that are clean, scalable and easy for stakeholders to understand.
 * Client Collaboration: Work closely with business and technical stakeholders to translate requirements into data solutions.
 * Quality & Governance: Apply best practices around data quality, lineage and documentation.


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