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.