Data Engineer

h3Function /h3 pWe'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. /p h3Responsibilities /h3 ul liTranslate architectural, security, GDPR and internal IT requirements into clear functional and technical specifications for data flows and reporting solutions. /li liCollaborate with Product Owners and Functional Analysts to identify business information needs and translate them into user stories with well-defined acceptance criteria. /li liEstablish consistent data definitions and KPI calculation logic through data dictionaries and semantic layers. /li liAct as the team's main point of contact for data engineering and BI-related topics, coordinating with developers, architects, testers and business stakeholders. /li liDesign, implement and monitor data quality controls covering completeness, accuracy, consistency and timeliness. /li liIntegrate quality checks into data loading processes, investigate anomalies and maintain documentation covering data lineage, models and processes. /li liMonitor and report on data quality performance to relevant stakeholders and management. /li liSet 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. /li liImplement monitoring and alerting mechanisms for data pipelines and batch processes, while supporting release, change and incident management. /li liDevelop and maintain ETL/ELT processes and reliable data publication layers for BI reporting. /li liContribute to the continuous improvement of the data platform, promoting reusable solutions and reducing unnecessary dependency on specific technologies. /li liPrepare well-documented, high-quality datasets with secure access controls to support future advanced analytics and AI initiatives. /li liEnsure end-to-end traceability of data, technical decisions, code and testing activities in line with internal governance and audit requirements. /li liContribute to information security, GDPR compliance and access management, including least-privilege principles and row-level security. /li /ul h3Technical Profile /h3 ul liBachelor's or Master's degree in ICT or a related field, or equivalent professional experience. /li liAt least 5 years of relevant experience in data engineering, data warehousing or Business Intelligence. /li liMinimum 2 years of experience working in a development team using CI/CD practices. /li liExpert-level SQL skills and solid knowledge of data modelling techniques, including Kimball and/or Data Vault, Slowly Changing Dimensions (SCD) and incremental loading. /li liProven experience with ETL/ELT processes and batch data processing. /li liHands-on experience with Git, branching strategies, code reviews and CI/CD tools such as GitHub Actions, Azure DevOps or GitLab CI. /li liExperience with automated testing and data quality frameworks, such as dbt tests or equivalent solutions. /li liKnowledge of monitoring and alerting mechanisms for data pipelines and processing activities. /li liExperience with BI tools such as SAS Visual Analytics, Power BI and/or Apache Superset, as well as semantic layer concepts. /li liWorking knowledge of SAS 9.4 is an advantage. /li liAdditional experience with Python, dbt, Docker and Azure is considered a plus. /li liFamiliarity with Jira and/or Azure Boards. /li liStrong analytical skills, attention to detail and a quality-driven mindset. /li liStructured, pragmatic and proactive, with a natural interest in automation and continuous improvement. /li liExcellent communication skills and the ability to translate complex or unclear business needs into practical technical solutions. /li liComfortable working with both technical and non-technical stakeholders. /li liAutonomous, collaborative and results-oriented, with the ability to operate effectively in a complex environment. /li liPrevious experience in the public sector is considered an asset. /li /ul h3Practical Information /h3 ul liLanguages: Fluent Dutch or French is required, together with an understanding of the other national language. Functional knowledge of English is also necessary. /li liCertifications: Relevant certifications are considered an advantage, including DAMA CDMP, data management or data quality certifications, cloud data engineering certifications and DevOps-related qualifications. /li /ul h3Contactperson Reference /h3 ul liReference #: INW28703 /li liMarilyn Weytens /li /ul