• Design, build, and maintain Power BI reports, datasets, and semantic models supporting NPS, TAC case analytics, EBV/EDW reconciliation, and customer health measurement.
• Develop and manage Power Automate workflows for automated insight delivery, including integration with AI-generated summary pipelines (GCP ESPv2 / API Gateway).
• Author and maintain DAX measures, calculation groups, and field parameters for complex, hierarchy-driven reporting across SAV, CAV, and UNIFIED_PARTY_ID structures.
• Collaborate with data engineering team members on Snowflake query optimization and dbt layer consumption, identifying and resolving model-layer issues that surface in report outputs.
• Partner with the broader analytics team to instrument parametric, configurable dashboard layers that support plug-and-play organizational hierarchy switching without requiring report rebuilds.
• Contribute to the team’s Microsoft Fabric readiness strategy, evaluating Direct Lake mode and OneLake integration patterns as the organization transitions its BI architecture.
• Provide thought leadership on AI-augmented analytics—including Copilot in Power BI, AI visuals, and LLM-integrated insight surfaces—aligned to the VP directive on AI future-readiness.

Minimum Qualifications

• 4+ years of hands-on Power BI development experience, including advanced DAX authoring, RLS implementation, incremental refresh configuration, and deployment pipeline management.
• Demonstrated experience designing and building Power Automate workflows that integrate with external APIs or cloud services for automated data delivery or alert distribution.
• Working proficiency in SQL with demonstrated ability to query and consume data from cloud data warehouses (Snowflake strongly preferred), including multi-level hierarchical aggregation patterns.
• Experience building and maintaining semantic data models (star or snowflake schema) that support multi-dimensional analytical reporting at enterprise scale.
• Foundational Python skills sufficient for data wrangling, parameterization scripting, or preprocessing tasks within an analytics pipeline context.

Preferred Qualifications

• Familiarity with Microsoft Fabric—including Lakehouse, OneLake, and Direct Lake mode—and awareness of how Fabric unifies Power BI with the broader data engineering stack.
• Experience incorporating AI capabilities into BI deliverables, including Copilot in Power BI, AI visuals (Key Influencers, Smart Narrative), or LLM-generated summaries surfaced within report interfaces.
• Exposure to GCP or Azure environments, including reading from BigQuery or consuming outputs from Cloud Run, API Gateway, or similar services.
• Experience with version control practices (Git) applied to analytics artifacts, including dbt model review, XMLA endpoint-based Power BI source control, or CI/CD pipeline awareness.
  • Strong data storytelling instincts—ability to translate complex CX metrics (NPS, case volume trends, customer health scores) into executive-ready visualizations without requiring prescriptive direction.