VP, Data and Analytics
New
United StatesFull-TimeVp
Salary240,000 - 260,000 USD per year
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Job Details
- Experience
- 15+ years
- Required Skills
- Data engineering
Requirements
- 15+ years of experience in Data and Analytics leadership roles
- 5+ years leading complex, high-volume enterprise data teams and large-scale ERP data environments
- Strong expertise in enterprise data strategy, architecture modernization, and analytics transformation
- Deep knowledge of Microsoft cloud data technologies, including Microsoft Fabric and Lakehouse architectures
- Extensive experience with data modeling, pipelines, BI tools, governance frameworks, and engineering best practices
- Proven track record leading organizational change and large-scale data transformation programs
- Strong understanding of AI integration and enterprise analytics capabilities
- Exceptional stakeholder management, communication, and executive presentation skills
- Ability to align technical execution with business strategy in complex environments
- Experience with JD Edwards (JDE) integrations is highly preferred
- DAMA-DMBOK certification or similar data governance accreditation is a plus
- Bachelor’s degree required; advanced certifications or graduate education are advantageous
Responsibilities
- Lead and oversee enterprise-wide data infrastructure, engineering, governance, and analytics operations across North America
- Define and execute a multi-year enterprise data strategy focused on modernization and scalability
- Drive the migration and transformation of legacy data systems into modern Microsoft Fabric architecture
- Build and lead high-performing cross-functional teams across multiple data disciplines
- Partner with executive leadership to align data initiatives with business priorities and strategic objectives
- Establish strong governance, DataOps practices, engineering standards, and observability frameworks
- Manage relationships with external consulting and technology partners
- Foster collaboration between data, engineering, operations, and data science teams globally
- Prepare enterprise data environments for AI integration
- Contribute to long-term technology roadmap planning and organizational transformation
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