Vice President, Business Intelligence Advanced Analytics

This mandate modernizes BI and establishesAI-driven BIas a core enterprise capabilityraising the standard for modeling and visualization operationalizing conversational analytics throughLLMsandDatabricks Genie and advancing the organization fromdescriptive and predictiveanalytics towardprescriptiveinsights. The role partners directly with senior leadership and carries enterprise-wide visibility and accountability to accelerate decision velocity drive adoption and maximize ROI through a durableinsight-to-action operating model.

As the Vice President Business Intelligence AI & Advanced Analytics within our enterprise analytics organization you will modernize BI and establish AI-promoten BI as a core enterprise capability.

Job responsibilities

• Serve as the primary BI partner to senior and executive stakeholders aligning analytics priorities to strategy surfacing forward-looking insights and influencing without authority to drive outcomes.

• Own requirements-to-value delivery across the BI lifecycle from problem framing and success criteria through UAT deployment adoption and impact measurement with clear ownership and SLAs.

• Architect and govern the semantic layer: define logical structures business rules and metric definitions for Engineering to implement; mentor the team on modeling trade-offs and performance optimization.

• Deliver AI-enabled BI: implement LLM-powered natural language querying (e.g. Databricks Genie) design domain-specific AI assistants and integrate predictive analytics into decision flows; progressively build prescriptive capabilities as maturity grows.

• Set and enforce visualization standards; personally build and review high-impact Sigma and Tableau assets that emphasize usability performance and guided analysis.

• Establish and run an insight-to-action governance model that prioritizes findings assigns accountable owners and tracks outcomes to closure; communicate benefits trade-offs and risks transparently to senior leaders.

• Define and track portfolio impact metrics including adoption decision velocity decision quality and ROI and apply disciplined risk-adjusted prioritization.

• Lead change management and enablement to drive adoption including training quick-reference content and executive-ready briefings.

• Build team capability through upskilling code and modeling reviews visualization critiques and recruiting hybrid talent with domain and technical depth.

• Maintain a continuous improvement backlog; iterate postgo-live based on feedback and decommission low-value artifacts.

Required qualifications capabilities and skills

• 10 yearsin BI/Analytics experience.

• 3 yearsleading teams deliveringenterprise-scale BI.

• Demonstrated expertise inlogical data modeling.

• Demonstrated expertise insemantic data modelingandsemantic layer design.

• Provenmetric stewardship(definition ownership consistency).

• Hands-on withSigmaandTableau includingperformance optimization.

• Buildsgoverned self-service analyticswithrow-level securitycontrols.

• Fluent inAdvanced SQLandPythonfor analytics engineering.

• Experience operationalizingLLMs/NLP/conversational AIinside BI workflows.

• Strongprompt engineeringcapability and familiarity with tools likeDatabricks Genie.

• Strengths indata governance/metadata managementapplied statistics & hypothesis testing rigorousrequirements decomposition/documentation andexecutive-ready communicationwith provensenior stakeholder managementand cross-functional influence.

Preferred qualifications capabilities and skills

• Experience deployingnatural-language queryingovergoverned data. Experience buildingdomain-specific AI assistantsaligned tobusiness taxonomy.

• Ability to map user intents tostandardized terms metrics and definitions. Proven track record ofdriving adoption at scaleacross teams.

• Demonstratedchange management and enablement(training comms documentation).

• Evidence that solutions operate withinsecurity/entitlements and governance controls.

• Stronger fit withmeasurable ROI(e.g. time saved reduced reporting faster decisions business impact).

• Ability to turn ambiguity into precise analytical problems and drive urgent insight-to-action with crisp executive communication and cross-functional influence across Business Finance Operations and Technology.