Senior Azure Data Engineer
Skills Required: Digital : Microsoft Azure
Job Description: Key Responsibilities
Pipeline Development: Design build and maintain efficient reusable and scalable ETL/ELT pipelines in Microsoft Fabric integrating data from SAP BW and other enterprise sources.
Data Product Engineering: Engineer standardized data products with strong focus on quality discoverability and reusability.
Automation Collaboration: Implement automation patterns and frameworks that accelerate data product creation.
Data Modelling: Develop and optimize semantic models star schemas and data warehouse structures to support reporting and analytics.
Governance & Quality: Ensure compliance with data governance lineage and quality standards; implement observability and monitoring for pipelines.
Performance Optimization: Troubleshoot and optimize pipelines ensuring high performance and reliability in production environments.
Continuous Improvement: Stay current with new features in Microsoft Fabric SAP integration methods and modern data engineering practices. Role Summary Kruger is seeking a Senior Data Engineer to design build and optimize scalable data pipelines and data products within our Microsoft Fabric and SAP BW ecosystem. This role will ensure data products are standardized governed and AI-ready serving as the backbone of Krugers Data Product Foundation. The Senior Data Engineer will collaborate with architects automation leads and business teams to deliver high-quality production-ready data solutions.
Qualifications
7 years of experience as a Data Engineer BI Engineer or similar role.
Strong expertise in Microsoft Fabric Data Factory Power BI and Data Lakehouse architectures.
Experience integrating and transforming data from SAP BW and ERP systems.
Experience with real-time data integration.
Advanced SQL Python Java C# KQL PowerShell scripts skills for data engineering and automation.
Proven track record of building and maintaining production-grade data pipelines at scale.
Familiarity with data governance lineage observability and Data Ops for data.
Strong collaboration skills with ability to work across technical and business teams.
Experience in performance tuning and optimization of large-scale data systems.
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