We are currently looking for a Business Intelligence Expert to work on the development and update of a data architecture strategy that adapts to evolving needs and accommodates both Business Intelligence and AI workloads at EU Institution based in Brussels (50% onsite).
Tasks:
- 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.
- 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.
Requirements:
- C1 level of English minimum. Any knowledge of French is an asset.
- Experience in migrating legacy data systems (SAP DataServices, SAS Data Integration, etc.) 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 understanding of Kubernetes.
- Knowledge of database systems, both relational (PostgreSQL, Oracle) and non-relational (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), 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.
- Excellent communication skills to articulate data architecture concepts to technical and non-technical stakeholders.
- Good knowledge of modelling tools.
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