✨ AI Summary
The Data and AI Solution Manager - Agentic AI role involves supporting enterprise analytics transformation initiatives. Key responsibilities include developing data models, building BI reports, automating reporting processes, and assisting with AI-powered analytics projects. This includes building data layers, developing data pipelines, ensuring data quality, implementing business dimensions, and maintaining KPI documentation. The role also requires building Power BI dashboards, developing operational reports, and supporting month-over-month analysis and report automation. Additionally, it involves configuring AI-powered reporting solutions, supporting prompt development and testing, and maintaining reusable AI skills. Governance tasks include performing data quality checks, supporting audit documentation, and adhering to security and RLS standards.
Requirements
Requires 2-5 years of experience in developing data models, building BI reports, automating reporting processes, and assisting in AI-powered analytics projects. Proficiency in Data pipelines, AI-powered analytics, KPI documentation, and Data quality validation is essential.
Description
Experience: 2–5 yearsOverviewSupports the implementation of enterprise analytics transformation initiatives by developing data models, building BI reports, automating reporting processes, and assisting in AI-powered analytics projects.ResponsibilitiesSemantic Model & Data EngineeringAssist in building Bronze, Silver and Gold data layers.Develop and maintain data pipelines.Support data quality validation and reconciliation.Implement standardized business dimensions and shared keys.Maintain KPI documentation.Business IntelligenceBuild Power BI dashboards and reports.Develop recurring operational reports.Support month-over-month analysis.Assist with report automation.AutomationSupport automated report scheduling.Build simple workflows using Power Automate.Maintain reporting templates.AI & AgentsAssist in configuring AI-powered reporting solutions.Support prompt development and testing.Help maintain reusable AI skills.GovernancePerform data quality checks.Support audit documentation.Follow security and RLS standards.