Data Engineer

Responsibilities

• Design, build, and maintain Power BI reports, datasets, and semantic models supporting NPS measurement, TAC case analytics, EBV/EDW reconciliation, and customer health scorecards.
• Author advanced DAX measures, calculation groups, and field parameters for complex, hierarchy-driven reporting across multi-level organizational structures (SAV → CAV → UNIFIED_PARTY_ID).
• Develop and manage Power Automate workflows for automated insight delivery, including integration with AI-generated summary pipelines and REST API-triggered distribution flows.
• Consume and validate dbt model outputs from Snowflake, diagnosing and resolving data-layer issues that surface as reporting errors-and collaborating with data engineers to address root causes upstream.
• Build parametric, configurable dashboard layers that support plug-and-play hierarchy switching without requiring report rebuilds when organizational structures change.
• Contribute to the team's Microsoft Fabric readiness strategy, evaluating Direct Lake mode, OneLake integration, and Fabric-native data flow patterns as the organization transitions its BI architecture.
• Adopt and champion AI-augmented BI capabilities including Copilot in Power BI, AI visuals, and LLM-integrated insight surfaces-aligned to the organization's AI future-readiness direction.

Requirements

• Objective, gate-level requirements. All five must be demonstrably met.
• 4+ years of hands-on Power BI development experience including advanced DAX authoring, row-level security implementation, incremental refresh configuration, deployment pipeline management, and workspace governance.
• Demonstrated experience designing and building semantic data models (star or snowflake schema) that support multi-dimensional analytical reporting at enterprise scale, including complex hierarchy structures.
• 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 and query performance awareness.
• Experience designing and maintaining Power Automate workflows that integrate with external APIs or cloud services for automated data delivery, alert distribution, or insight pipeline triggering.
• Foundational Python skills sufficient for data wrangling, parameterization scripting, or preprocessing tasks that feed into a Power BI or analytics pipeline context.
• Familiarity with Microsoft Fabric-including Lakehouse, OneLake, and Direct Lake mode-and the ability to articulate how Fabric changes the Power BI architectural model relative to a Snowflake-backed dataset.
• Experience incorporating AI capabilities into BI deliverables: Copilot in Power BI, AI visuals (Key Influencers, Decomposition Tree, Smart Narrative), or LLM-generated summaries surfaced within report interfaces.
• Working knowledge of dbt model consumption-sufficient to read ref() dependencies, understand test frameworks, and diagnose issues where dbt layer changes break downstream semantic models.
• Exposure to GCP or Azure services used in data pipeline contexts (Cloud Run, API Gateway, Azure Data Factory), with ability to trace data lineage from source API through to a Power BI report surface.
• Version control practices applied to analytics artifacts: Git-based workflows, Power BI XMLA-endpoint source control, or CI/CD pipeline awareness for BI deployment.
• Why Cisco?
• At Cisco, we're revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond. We've been innovating fearlessly for 40 years to create solutions th

Benefits

Additional Information

Meet the Team The CIA with Data and Analytics organization at Cisco owns the intelligence infrastructure that translates customer signals into strategic insight across Cisco's global portfolio. Our team sits at the intersection of data engineering, business intelligence, and AI-augmented analytics-delivering the reporting platforms, data products, and insight pipelines that inform decisions at the VP and SVP level. The India-based engineering team is a core delivery engine within this organization, operating end-to-end on modern data and BI infrastructure. Engineers here work closely with US-based analytics leads and architects on a modern stack that spans Snowflake, dbt, Python, Power BI, and Microsoft Fabric. This is a high-ownership environment where individual contributors shape the tools and platforms that the broader organization depends on.

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Company Intel

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