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# Data Engineer

- **Company:** darwind
- **Location:** Brussels Metropolitan Area, Belgium
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Systems, Data Warehousing, Digital Architecture, Python (Programming Language), SQL Databases, Unstructured Data, Information Technology, Real Time Data, Data Management, Data Pipelines
- **Published:** September 12, 2026
- **Apply:** https://www.adzuna.be/details/5879867415

## About the Role

We look beyond the CV. For us, motivation and curiosity matter just as much as the technical box-ticking, but to thrive in this role, you'll likely recognise yourself in most of the following:

 * You hold a master's degree in computer science, data engineering, IT or a related field
 * You have at least 4 years of experience as a Data Engineer in an IT environment
 * You are proficient in Python and SQL and have solid experience building data pipelines
 * You have hands on experience with ETL or ELT tools
 * Familiarity with big data tools
 * You have working knowledge of cloud platforms such as AWS, Azure or GCP
 * You think in systems, you are a strong problem solver, and you document your work clearly
 * You are fluent in Dutch, French is a plus

## Description

As Data Engineer, you'll design and maintain the data infrastructure that IT and business teams rely on to work with reliable, accessible data. Concretely, you will:

 * Design, build and maintain scalable ETL and ELT pipelines for structured and unstructured data
 * Set up and manage batch and real time data ingestion from multiple internal and external sources
 * Build and optimise data models and data warehouses that support analytics and reporting needs
 * Work with cloud platforms such as AWS, Azure or GCP to deploy and scale data infrastructure
 * Implement monitoring, alerting and quality checks to keep pipelines and data reliable
 * Collaborate closely with data analysts, data scientists and business stakeholders to understand data needs
 * Optimise the performance, scalability and cost efficiency of existing data systems
 * Document architecture, workflows and technical decisions in a clear and structured way
 * Stay up to date with new tools, frameworks and best practices in the data engineering field


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