Lead Data & BI Engineer (Azure / Microsoft BI Stack) – Short-Term Engagement

Nasze wymagania: Minimum 6+ years of experience in Data Engineering / BI Engineering roles Azure Analysis Services (AAS) Microsoft SQL Server Power BI Multidimensional data models (OLAP cubes) Experience with data pipeline troubleshooting and optimization Strong understanding of data warehouse modeling (fact/dimension design) Experience diagnosing data integrity and ETL issues Ability to redesign and stabilize complex analytical processing pipelines Strong analytical and problem-solving skills in BI environments O projekcie: We are seeking a Senior / Lead Data & BI Engineer with strong expertise in the Microsoft BI stack to support a short-term engagement focused on stabilizing and redesigning a failing analytical pipeline. The current architecture loads data from Microsoft SQL Server into Azure Analysis Services (multidimensional model), which is then consumed by Power BI reports. The processing pipeline currently experiences frequent failures caused by issues related to data modeling, data integrity, incorrect join logic, and cube design. The selected engineer will be responsible for diagnosing the root causes of these failures, redesigning the data model where necessary, and ensuring stable cube processing and reliable reporting performance. Engagement duration: 2–3 months. Zakres obowiązków: Analyze and troubleshoot the existing SQL Server → Azure Analysis Services data processing pipeline Identify and diagnose root causes of cube processing failures Resolve issues related to: incorrect join logic, duplicate records, null value handling, incorrect key relationships, inconsistencies between fact and dimension tables Review and redesign multidimensional models in Azure Analysis Services Improve fact/dimension modeling and relationships Refactor ETL logic responsible for feeding the analytical cube Ensure data integrity and consistency across dimensions, measures, and reporting layers Optimize cube processing and improve overall reporting performance in Power BI