Vice President of Data Analytics & Business Intelligence
Listed on 2026-07-20
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IT/Tech
Business Intelligence, Data Analyst, Data Warehousing, Business Systems & Technology Analysis
The VP of Data Analytics & Business Intelligence is responsible for defining and executing the enterprise data and analytics strategy to enable data-driven decision‑making across the organization. This executive leader oversees Enterprise Data Warehouse and Business Intelligence to deliver trusted, scalable, and actionable business insights.
This role drives the development of a modern analytics ecosystem that transforms enterprise data into strategic business value by improving data integrity, operational excellence, customer experience, financial performance, and innovation. The VP also provides executive leadership for establishing standardized processes, governance, prioritization, and continuous improvement to ensure consistent, high-quality delivery of analytics solutions.
Essential Job Functions Strategic Leadership- Develop and execute the enterprise data and analytics strategy aligned with corporate objectives.
- Partner with executive leadership to identify opportunities to improve operational performance, profitability, customer experience, and business growth through data-driven insights.
- Foster an enterprise-wide data‑driven culture through governance, education, and executive engagement.
- Evaluate emerging technologies and industry trends to continuously modernize the analytics platform.
- Establish enterprise data governance standards to ensure trusted, secure, accurate, and consistent data across the organization.
- Lead initiatives focused on data quality, master data management, metadata management, and data stewardship.
- Develop governance policies supporting regulatory compliance, privacy, security, and audit requirements.
- Partner with IT Security and Compliance teams to safeguard enterprise data assets.
- Lead the strategy, architecture, implementation, and optimization of the Enterprise Data Warehouse and enterprise data platform.
- Establish enterprise data models, master data management, metadata standards, and semantic layers to ensure consistent reporting.
- Ensure the security, reliability, scalability, and performance of enterprise data platforms.
- Drive modernization initiatives utilizing technologies such as Snowflake, Microsoft Fabric, Azure Data Platform, Databricks, SQL Server, Power BI, Tableau, and other cloud-native solutions.
- Lead the delivery of enterprise dashboards, executive scorecards, KPI reporting, and operational analytics.
- Develop predictive, prescriptive, and AI-enabled analytics that improve business performance and decision‑making.
- Establish enterprise standards for reporting, visualization, and self‑service analytics.
- Promote responsible adoption of AI and machine learning to enhance operational efficiency and business outcomes.
- Implement standardized processes for demand intake, prioritization, roadmap planning, estimation, delivery, and release management.
- Partner with business stakeholders to define product vision, business priorities, and measurable outcomes.
- Drive continuous improvement through Agile methodologies, Dev Ops, CI/CD, automation, quality assurance, and delivery metrics.
- Foster a culture of operational excellence, accountability, innovation, and customer‑focused delivery.
- Serve as the executive advisor to business leaders on enterprise analytics and reporting strategy.
- Translate complex analytical findings into actionable business recommendations.
- Support strategic planning, budgeting, forecasting, pricing, customer analytics, network optimization, and operational performance initiatives.
- Present enterprise analytics strategy, business insights, and performance metrics to executive leadership.
- Build, lead, and develop a high‑performing organization across Data Engineering, Business Intelligence, Analytics Engineering, and Enterprise Reporting.
- Foster a culture of innovation, collaboration, accountability, continuous learning, and operational excellence.
- Develop organizational capabilities through coaching, succession planning, and talent development.
- Promote enterprise-wide data literacy and adoption of…
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