Hybrid Cloud Data Architect

For an European institution in Brussels, Belgium, we are looking for a hybrid Cloud Data Architect. Candidates need to have experience in migrating legacy data systems (SAP DataServices, SAS Data Integration) to a modern cloud-based, open-source data platform solution (preferably Data Lakehouse).

Candidates need to be based in Belgium or willing to relocate to Brussels, when coming from abroad. Candidates need to be willing to work 5 days on-site.

Candidates need to be fluent in English. A work permit is not provided. This position is open for contractors.

Tasks and Responsibilities:

• Develop and update a data architecture strategy that adapts to evolving needs and accommodates both Business Intelligence and AI workloads;
• Design and implement architectures for the cloud that are vendor agnostic;
• Design a modern scalable data platform to replace a large legacy data system in a phased approach;
• Align architectural decisions with data governance policies and the department’s vision on cloudification;
• Establish and enforce data management policies and processes, including data quality, security and platform health monitoring;

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• Ensure regulatory compliance and adherence to audit requirements;
• Provide guidance and mentorship to data analysts and data engineers;
• Facilitate change management by guiding colleagues and users through the migration process;
• Document and maintain data architecture and data assets in detail;
• Assistance with deployment, configuration and testing of the system;
• Participation in meetings with other project teams;

Profile:

• Bachelor or Master degree;
• +13 years of IT experience;

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• Experience in migrating legacy data systems (SAP Data Services, SAS Data Integration) to a modern cloud-based, open-source data platform solution (preferably Data Lakehouse);
• Excellent knowledge of designing scalable and flexible modern cloud-based and open-sources data architectures;
• Experience with AI-powered assistants like Amazon Q for innovative data solutions design;
• Strong exposure with Kubernetes;
• Previous experience with relational and non-relational database systems (PostgreSQL, Oracle or Elasticsearch, MongoDB);
• Experience with ETL/ELT processes and related data ingestion and transformation tools (like Spark, dbt, Trino);
• Proficiency in data pipeline orchestration tools (like Airflow, Dagster, Luigi);
• Knowledge of data governance frameworks and tools (like DataHub, Open Metadata);
• Familiarity with data quality management, data security, access control and regulatory compliance;
• Proficiency with system-to-system integration via RESTful APIs;
• Experience with DevSecOps practices and tools related to data pipelines, including CI/CD for data infrastructure;
• Good knowledge of modelling tools;
• Fluent in English;