BI Data Engineer
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Key Responsibilities
• Design, develop, and maintain Enterprise Data Warehouses (EDW), Data Lakes, and Data Lakehouse solutions across cloud, on-premises, and hybrid environments.
• Build, optimize, and maintain ETL/ELT pipelines, data integration processes, orchestration workflows, and data virtualization solutions.
• Design scalable data models and BI architectures aligned with business and reporting requirements.
• Develop and maintain dashboards, KPIs, reports, and self-service BI solutions that support data-driven decision-making.
• Optimize database and platform performance through query tuning, indexing, partitioning, caching, and resource optimization.
• Implement data quality, observability, lineage, cataloguing, and governance practices.
• Ensure data solutions comply with GDPR, security, and organizational data governance standards.
• Define and implement testing strategies to ensure the reliability and quality of data pipelines and BI solutions.
• Automate deployments and platform management using CI/CD and Infrastructure as Code (IaC) practices.
• Maintain comprehensive technical documentation covering data models, pipelines, architectures, and BI solutions.
• Support data stewardship initiatives and help business users make effective use of certified datasets and self-service BI tools.
• Provide guidance and training to business stakeholders on data and BI solutions. Qualifications What We're Looking For:
• University degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, or a related field, or equivalent professional experience.
• Strong knowledge of Enterprise Data Warehouse (EDW) architecture and design, including dimensional modelling and star/snowflake schemas.
• Hands-on experience with Data Lake and Data Lakehouse architectures and modern analytics platforms.
• Strong proficiency in SQL and relational databases, with knowledge of NoSQL technologies being an advantage.
• Experience with BI, reporting, analytics, ETL/ELT, and data pipeline technologies, such as:
• Power BI
• Tableau
• Qlik
• dbt
• Informatica
• Talend
• Azure Data Factory
• Solid understanding of data modelling, OLAP, data integration, near-real-time data ingestion, and Change Data Capture (CDC).
• Experience working with cloud-based data and BI platforms.
• Knowledge of data governance, data lineage, data cataloguing, and data observability.
• Good understanding of data security and GDPR compliance.
• Excellent English communication skills; French is considered a plus.
• Relevant certifications are a strong advantage, such as:
• Microsoft Certified: Power BI Data Analyst Associate
• Microsoft Certified: Azure Data Engineer Associate
• AWS Certified Data Analytics – Specialty
• Equivalent data engineering or BI certifications.
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