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# AI/Data Engineer

- **Company:** Vivid Resourcing
- **Location:** Antwerpen, Belgium
- **Salary:** €66,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Microsoft Azure, Big Data, BigQuery, Cloud Computing, Continuous Integration, Extract Transform Load (ETL), Data Warehousing, Data Flow Control, Python (Programming Language), SQL Databases, Workflow Management Systems, Data Processing, Freeform SQL, Google Cloud, Large Language Models, Kubernetes, Machine Learning Operations, Terraform, GPT, Data Pipelines, Databricks
- **Published:** September 8, 2026
- **Apply:** https://www.collegerecruiter.com/job/2851196796-aidata-engineer

## About the Role

* Proven experience building and maintaining ETL/data pipelines at scale
 * Experience or strong interest in AI/ML integration - LLMs, model deployment, or MLOps
 * Hands-on experience with GCP and/or Azure (BigQuery, Dataflow, Data Factory, Databricks, etc.)
 * Comfort working across the modern data stack (orchestration tools, warehousing, CI/CD)
 * Dutch language skills preferred; English required
 * A curious, problem-solving mindset and appetite to work broadly across the data/AI/cloud landscape

Nice to have

 * Certifications in GCP or Azure
 * Experience with Terraform/IaC, Airflow, dbt, or Kubernetes
 * Exposure to LLM frameworks (LangChain, OpenAI/Anthropic APIs, etc.)

## Description

We're looking for a versatile AI & Data Engineer to join our team in Antwerp. If you love building robust ETL pipelines, writing clean Python and SQL, and want your work to directly power real AI applications running on modern cloud infrastructure, this is your role.

What you'll do

 * Design, build, and optimize ETL/ELT pipelines that turn messy data into reliable, analytics-ready assets
 * Develop and integrate AI/ML-powered features into data workflows and products
 * Write clean, efficient Python for automation, data processing, and pipeline orchestration
 * Craft and optimize complex SQL queries across large-scale datasets
 * Architect and manage supporting cloud infrastructure across Google Cloud Platform (GCP) and Microsoft Azure
 * Collaborate with data scientists, analysts, and product teams to translate business needs into technical solutions
 * Champion best practices in data quality, security, and cost-efficient architecture


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