Green Mountain

Platform Engineer

• Design, build, and maintain Power BI dashboards, reports, semantic models, KPIs, and analytics assets for internal and customer-facing use cases
• Engineer scalable Microsoft Fabric and Power BI solutions for analytics and reporting modernization initiatives
• Develop reusable semantic models, data marts, report templates, and dashboard design patterns
• Partner with Product, Operations, Customer Success, Data Engineering, Architecture, and AI Engineering teams
• Migrate and modernize legacy analytics and reporting assets into Power BI and Microsoft Fabric
• Translate customer and business reporting needs into scalable Power BI and Fabric solutions
• Establish governance for workspace design, report definitions, KPI logic, semantic models, security, and operational support
• Implement access controls, Row-Level Security, workspace governance, and deployment checks
• Validate reports, data models, calculations, filters, security roles, and refresh processes before release
• Improve delivery through reusable templates, automation, deployment pipelines, performance tuning, and Microsoft Fabric capabilities
• Support AI-enabled analytics experiences, including Copilot in Power BI, Data Agents, conversational analytics, and natural language-driven insights
• Provide technical mentoring and peer guidance to engineers, analysts, and business users

Analytics Platform Engineer

Full-stack Engineer

• Lead the design, development, and operationalization of AI-enabled product capabilities, including conversational analytics, intelligent workflow automation, Data Agents, and AI-assisted decision support experiences
• Partner with Product, Architecture, Analytics, Engineering, Operations, and Customer Success teams to translate customer and business challenges into production AI solutions
• Define AI product requirements, solution patterns, success metrics, release readiness criteria, and adoption measures aligned with GMT's technology roadmap
• Develop reusable AI engineering patterns for prompt engineering, retrieval-augmented generation, agentic workflows, model evaluation, monitoring, observability, and secure integrations
• Establish quality, governance, security, and responsible AI practices
• Collaborate with internal engineering teams and external partners to deliver secure, explainable, and supportable AI products
• Drive customer self-service and time-to-insight improvements through natural language experiences and AI-enabled analytics
• Evaluate emerging AI technologies and recommend practical adoption paths
• Define product impact measurements including adoption, usage, trust, productivity improvements, and value realization
• Provide technical mentoring and leadership to engineers working on AI-enabled products and platform capabilities

Analytics Platform Engineer

AI Product Engineer