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Business Intelligence Developer

Power International Holding · Doha, Qatar

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Power International Holding is looking for an experienced Business Intelligence (BI) Developer to join our EPMO team.The successful candidate will play a key role in transforming complex project, financial, commercial and operational data into meaningful dashboards, executive reports and actionable insights to support strategic decision-making across the Group.

Key Responsibilities

Design, develop and maintain interactive Power BI dashboards and executive-level reports.Translate business requirements into effective reporting solutions, KPIs and performance metrics.Develop advanced DAX measures, Power Query transformations and reporting logic.Build project performance dashboards covering earned value, cost, schedule, progress, cash flow and procurement.Develop portfolio-level reporting with drill-down capabilities across subsidiaries, sectors and projects.Manage Power BI workspaces, deployment pipelines, scheduled refreshes and report security.Ensure consistency, accuracy and governance across reporting and KPI definitions.Leverage AI-assisted analytics and Microsoft Copilot to enhance reporting capabilities.Qualifications & Experience:Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering or a related discipline.5–8 years of experience in Business Intelligence or Reporting Development.Minimum 4 years of hands-on Power BI development experience.Advanced expertise in DAX, Power Query (M), SQL and data visualisation.Experience developing executive-level dashboards and automated reporting solutions.Exposure to construction, infrastructure, EPC, real estate or large-scale project environments.Familiarity with SAP, Primavera P6 and Microsoft Fabric will be an advantage.Microsoft PL-300 certification is preferred.AI Fluency – Essential RequirementCandidates must demonstrate practical experience using AI or Microsoft Copilot in their BI development work, such as developing or validating reports and measures, identifying errors, or improving analytical efficiency.