Own the design, development, and delivery of business intelligence solutions that span Cisco’s global customer experience programs.
Build and maintain Power BI semantic models and dashboards that feed directly into executive reporting and operational decision-making—working across a Snowflake/dbt data architecture and integrating with AI-driven insight delivery pipelines.
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.
Requirements
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.