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Microsoft Fabric & Data Engineering
• Act as a senior technical authority for Microsoft Fabric and Power BI across end-to-end data and analytics scenarios.
• Design and implement Fabric solutions using OneLake, Lakehouse, Data Warehouse, Data Factory pipelines, Dataflows Gen2, notebooks, and semantic models.
• Ingest, transform, and orchestrate data from cloud, on-premises, structured, semi-structured, and streaming sources.
• Use SQL and PySpark for data preparation and transformation; use KQL where real-time analytics scenarios require it.
• Design scalable data architectures, loading patterns, medallion-style data layers, and reusable governed data products.
• Implement and optimize Fabric workloads for performance, reliability, monitoring, security, and cost-effective capacity usage.
• Apply source control, deployment pipelines, CI/CD practices, and development lifecycle controls for analytics solutions.
• Advise customers on migration and modernization from existing Power BI, Azure Synapse, Azure Data Factory, and related analytics environments to Microsoft Fabric.
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Power BI & Analytics Engineering
• Design and implement enterprise Power BI solutions, including semantic models, DAX measures, reports, dashboards, and reusable datasets.
• Prepare and enrich data for analysis across Fabric lakehouses, warehouses, and other approved data sources.
• Implement and manage semantic models using appropriate Import, DirectQuery, and Direct Lake patterns.
• Troubleshoot complex model, refresh, query, report, and capacity performance issues.
• Advise on dimensional modeling, DAX optimization, report design standards, workspace strategy, and self-service BI governance.
• Translate business requirements into secure, scalable, and maintainable analytics solutions for business users and AI-enabled scenarios.
Key Responsibilities - Delivery & Advisory
• Deliver high-quality hands-on customer engagements, including workshops, architecture and design sessions, assessments, proofs of concept, pilots, optimization engagements, and production deployments.
• Lead technical discovery, define target architectures, identify risks and dependencies, and agree practical paths to production.
• Provide technical guidance across data integration, data engineering, analytics engineering, BI, governance, and operational readiness.
• Produce clear technical documentation, architecture decisions, implementation guidance, and reusable delivery assets.
• Contribute to technical readiness, intellectual property, knowledge sharing, and Global Delivery best practices.
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Collaboration & Leadership
• Collaborate with CSAMs, Global Delivery CSAs, partner teams, and customer stakeholders to support successful delivery and adoption.
• Act as a trusted technical advisor to senior customer stakeholders and communicate complex topics clearly to technical and business audiences.
• Mentor engineers, review technical designs and deliverables, and contribute to team readiness.
• Ensure solutions align with applicable Microsoft security, compliance, privacy, and data governance guidance.