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Job Description:

The Senior Manager, Business Intelligence provides strategic leadership for enterprise reporting and analytics, ensuring business intelligence capabilities scale with organizational growth. This role sets the vision for KPI governance, data products, and self-service analytics, and leads managers and senior individual contributors to deliver measurable business impact. The ideal candidate is a strong leader and operator with deep BI expertise across Databricks and modern visualization platforms (Tableau/Power BI), capable of aligning stakeholders, maturing operating models, and advancing analytics standards.

Key Responsibilities

·         Strategic leadership: Define the enterprise BI strategy, operating model, and multi-quarter roadmap aligned to business priorities and data platform direction.

·         People leadership: Lead and develop BI leaders, building a high-performing team and healthy talent pipeline.

·         Stakeholder engagement: Partner with the PEX/S2C/SMS GPO organizations to establish enterprise KPI governance, standard metric definitions, and reporting hierarchies to ensure consistent measurement across functions.

·         Strategic leadership: Establish and enforce responsible AI governance for BI (policies, approval workflows, model/tool standards, validation and monitoring expectations) to ensure compliant, trustworthy AI-assisted insights at scale.

·         Cross-functional collaboration: Partner with Data Management to deliver scalable, governed data products leveraging Databricks and enterprise data platforms.

·         Agile leadership: Drive adoption of self-service analytics through semantic models, enablement, and clear documentation, reducing dependency on ad hoc requests.

·         Strategic leadership: Set the strategy for AI-enabled self-service and conversational analytics (natural language to governed metrics), ensuring alignment to the semantic layer, KPI governance, and adoption goals.

·         Technical excellence: Oversee the design standards and user experience of Tableau/Power BI solutions, conversational business intelligence, ensuring persona-based insights and consistent visual language.

·         Accountability: Create performance management and service-level expectations for BI delivery (quality, timeliness, uptime, and stakeholder satisfaction).

·         Business management: Manage budget, vendor/partner relationships, and tool strategy as applicable; evaluate and implement capabilities to improve efficiency and governance.

Qualifications

·         Bachelor’s degree in Information Systems, Computer Science, Business Analytics, Statistics, or a related field (Master’s preferred).

·         10+ years of experience in business intelligence, analytics, and/or data engineering, including enterprise-scale BI delivery.

·         5+ years of leadership experience, including managing managers and leading cross-functional initiatives.

·         Strong understanding of data platform patterns, data modeling, and governance, including experience with Databricks.

·         Expertise in Tableau and/or Power BI at an enterprise level (architecture, standards, performance, security, and adoption).

·         Proven ability to align executives and stakeholders to a shared measurement framework and to communicate complex insights clearly.

·         Demonstrated procurement domain expertise, including partnering with S2C/P2P process owners to standardize KPI definitions, reporting hierarchies, and measurement governance.

·         Understanding of procurement controls and compliance expectations (e.g., auditability, access controls, segregation of duties) and how they influence analytics design and distribution.

·         Proven ability to lead responsible adoption of AI-assisted analytics and data management (including Generative AI) by setting guardrails, governance, and validation standards that protect data and improve decision quality.

Preferred Skills

·         Experience designing and implementing enterprise semantic layers (e.g., tabular models) and standardized KPI hierarchies.

·         Demonstrated success building self-service analytics programs, including training, community of practice, and governance.

·         Experience with data quality frameworks (testing, monitoring, and SLAs) and analytics product management practices.

·         Demonstrated AI and agentic model building for the business intelligence and insights

·         Familiarity with privacy, regulatory, and security requirements impacting analytics (role-based access, row-level security, and auditing).

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