Data Engineer

Function

We're looking for an experienced Data Engineering professional to join our client's development team and contribute to large-scale digital transformation initiatives. In this role, you'll act as the bridge between business requirements and technical implementation, ensuring reliable data flows, high-quality reporting and robust data management practices. You'll play an important role in strengthening data quality, traceability, automation and DevOps processes throughout the entire data lifecycle.

Responsibilities

• Translate architectural, security, GDPR and internal IT requirements into clear functional and technical specifications for data flows and reporting solutions.
• Collaborate with Product Owners and Functional Analysts to identify business information needs and translate them into user stories with well-defined acceptance criteria.
• Establish consistent data definitions and KPI calculation logic through data dictionaries and semantic layers.
• Act as the team's main point of contact for data engineering and BI-related topics, coordinating with developers, architects, testers and business stakeholders.
• Design, implement and monitor data quality controls covering completeness, accuracy, consistency and timeliness.
• Integrate quality checks into data loading processes, investigate anomalies and maintain documentation covering data lineage, models and processes.
• Monitor and report on data quality performance to relevant stakeholders and management.
• Set up and maintain CI/CD pipelines for data processes, models and reports, including Git-based version control, branching strategies, code reviews, automated testing and controlled deployments.
• Implement monitoring and alerting mechanisms for data pipelines and batch processes, while supporting release, change and incident management.
• Develop and maintain ETL/ELT processes and reliable data publication layers for BI reporting.
• Contribute to the continuous improvement of the data platform, promoting reusable solutions and reducing unnecessary dependency on specific technologies.
• Prepare well-documented, high-quality datasets with secure access controls to support future advanced analytics and AI initiatives.
• Ensure end-to-end traceability of data, technical decisions, code and testing activities in line with internal governance and audit requirements.
• Contribute to information security, GDPR compliance and access management, including least-privilege principles and row-level security.

Technical Profile

• Bachelor's or Master's degree in ICT or a related field, or equivalent professional experience.
• At least 5 years of relevant experience in data engineering, data warehousing or Business Intelligence.
• Minimum 2 years of experience working in a development team using CI/CD practices.
• Expert-level SQL skills and solid knowledge of data modelling techniques, including Kimball and/or Data Vault, Slowly Changing Dimensions (SCD) and incremental loading.
• Proven experience with ETL/ELT processes and batch data processing.
• Hands-on experience with Git, branching strategies, code reviews and CI/CD tools such as GitHub Actions, Azure DevOps or GitLab CI.
• Experience with automated testing and data quality frameworks, such as dbt tests or equivalent solutions.
• Knowledge of monitoring and alerting mechanisms for data pipelines and processing activities.
• Experience with BI tools such as SAS Visual Analytics, Power BI and/or Apache Superset, as well as semantic layer concepts.
• Working knowledge of SAS 9.4 is an advantage.
• Additional experience with Python, dbt, Docker and Azure is considered a plus.
• Familiarity with Jira and/or Azure Boards.
• Strong analytical skills, attention to detail and a quality-driven mindset.
• Structured, pragmatic and proactive, with a natural interest in automation and continuous improvement.
• Excellent communication skills and the ability to translate complex or unclear business needs into practical technical solutions.
• Comfortable working with both technical and non-technical stakeholders.
• Autonomous, collaborative and results-oriented, with the ability to operate effectively in a complex environment.
• Previous experience in the public sector is considered an asset.

Practical Information

• Languages: Fluent Dutch or French is required, together with an understanding of the other national language. Functional knowledge of English is also necessary.
• Certifications: Relevant certifications are considered an advantage, including DAMA CDMP, data management or data quality certifications, cloud data engineering certifications and DevOps-related qualifications.

Contactperson & Reference

• Reference #: INW28703
• Marilyn Weytens
• marilyn.weytens@i4m.be