BI Data Engineer

Tasks and Responsibilities
• Enterprise Data Warehouse (EDW): Create and maintain the eGrants Enterprise Data Warehouses (EDW).
• BI Architecture Design: Design Business Intelligence (BI) architectures (e.g., data warehouse, data lakehouses) for cloud, on-premises, and hybrid environments, ensuring compliance with security and data residency requirements.
• Business Requirements Analysis: Gather and analyse business requirements specifically for data pipelines, storage, and reporting solutions.
• ETL Processes and Orchestration: Design and implement modern Extract, Transform, Load (ETL) processes and orchestration workflows, incorporating data contracts and schema evolution management.
• Data Modelling: Design and implement data models (e.g., dimensional modelling) to support reporting and analytics, ensuring alignment with business requirements.
• Reporting and Analytics: Design and build reporting and analytics applications, creating dashboards, KPIs, and self-service BI tools that deliver actionable insights to business stakeholders.
• Data Quality and Monitoring: Design and implement data quality frameworks and health monitoring processes that include data observability (lineage, freshness) and defined Service Level Agreements/Service Level Objectives (SLAs/SLOs).
• Testing and CI/CD: Define and execute test programs for BI solutions, including data validation, regression tests, contract tests, and automated pipelines integrated into CI/CD.
• Technical Documentation: Produce and maintain technical documentation (data dictionaries, lineage, design specifications, runbooks) to support transparency, governance, and audit readiness.
• BI Semantic Layer: Govern the BI semantic layer (KPIs, metrics catalog, naming conventions, row-level security) to ensure consistency and trusted insights.
• Performance and Cost Optimization: Optimize cost and performance of BI platforms and warehouses (partitioning, caching, clustering, query optimization, resource scaling).
• Self-Service BI: Enable self-service BI capabilities for business users through curated datasets, certified reports, and training/support. Requirements
• University degree in IT combined with relevant IT professional experience of at least 10 years.
• At least 10 years of practical experience with SAP Business Objects is required.
• At least 8 years of practical experience with SAP Data Services is also required.
• Excellent knowledge of enterprise data warehouse design and architecture, including dimensional modelling and star/snowflake schema design.
• Excellent knowledge of relational database systems applied to data warehousing.
• Excellent knowledge of SQL and PL/SQL.
• Excellent knowledge of BI reporting and analytics tools (e.g., SAP Business Objects, Power BI, Tableau, Qlik) for enterprise dashboards and self-service analytics.
• Excellent knowledge of ETL and ELT tools (e.g., SAP Data Services, Informatica, Talend, dbt, Azure Data Factory) to manage enterprise data pipelines.
• Knowledge of non-relational databases (e.g., MongoDB, Cassandra, Hadoop HBase) for handling unstructured and semi-structured data would be an asset.
• Knowledge of SAP BO universe design and SAP BO administration.
• Knowledge of data lake and lakehouse design patterns (e.g., Delta Lake, Apache Iceberg) to support large-scale analytics would be an asset.
• Knowledge of modelling tools to design data models.
• Knowledge of OLAP technologies and data mining tools.
• Knowledge of cloud BI architectures (e.g., Azure Synapse, Snowflake, AWS Redshift) to enable scalable analytics would be an asset.
• Excellent command of the English language; French will be considered an asset.