Business Intelligence (BI) Data Analysis Experienced Professional

Design, develop, test, publish and maintain interactive Power BI reports and dashboards for business, operational, process and automation use cases,

• Translate business questions and operational needs into meaningful KPIs, analytical views, visualizations and reusable reporting templates,

• Develop scalable semantic models using dimensional modeling and star-schema practices with documented calculations, filters, assumptions and business rules,

• Create DAX and Power Query calculations, optimize report performance, refresh times, model size, usability and maintainability,

• Implement appropriate report and data security, including row-level security where required, and validate outputs against source systems,

• Analyze workflow, activity and operational data to identify patterns, bottlenecks, process variations, rework, manual effort and improvement opportunities,

• Establish baseline measures and measure changes in cycle time, process quality, manual effort, workflow variation and agreed outcomes,

• Support Microsoft Fabric workspace structure, naming conventions, ownership, access controls, capacity visibility, workload monitoring and lifecycle standards,

• Support Fabric pipelines, lakehouses, warehouses, semantic models, notebooks, dataflows and Power BI content across development, test and production environments,

• Build and maintain data-ingestion, transformation and orchestration pipelines from approved enterprise systems, databases, APIs, files, cloud platforms and business applications,

• Perform data profiling, cleansing, normalization, transformation, validation, reconciliation, error handling, exception monitoring and pipeline logging,

• Prepare trusted and governed data products for AI, automation, proof-of-concept, MVP, pilot and production initiatives,

• Develop dashboards to measure AI and automation adoption, operational outcomes, benefits realization and process improvement impact,

• Partner with global and regional stakeholders, process owners, IT, data engineers, solution architects, automation developers, governance teams and business teams,

• Create and maintain technical documentation, support guides, data dictionaries, source-to-target mappings, lineage, dependencies, refresh schedules and known limitations,

• Follow information security, privacy, retention, confidentiality, responsible AI, role-based access and least-privilege principles,

• Support UAT, production releases, troubleshooting, demonstrations, knowledge transfer, user guides, training materials and continuous improvement.

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