Vice President, Data Architecture, Engineering & AI (Remote)

About the Role

As Vice President, Data Architecture, Engineering & AI you will be responsible for driving the vision, strategy, and execution of data products that enable business growth, operational efficiency, and customer-centric innovation. This role partners closely with business and technology leaders to transform data into a strategic asset, delivering scalable, reliable, and user-friendly data solutions.

What You'll Do

• Define and own the data product and technical data science strategy, aligning with enterprise technology and business priorities
• Lead the design, development, and lifecycle management of data products that support business operations, customer insights, and innovation
• Build and scale data science capabilities, including machine learning, AI-driven solutions, and advanced analytics to optimize retail operations and customer engagement
• Partner with business units, analytics, engineering, and product management to prioritize high-value use cases for both data products and data science applications
• Oversee data governance, stewardship, and metadata management to ensure accuracy, compliance, and trust
• Champion modern data and AI architectures, including cloud-native platforms, APIs, data streaming services, and real-time analytics
• Drive data democratization, ensuring business users can easily discover, access, and leverage insights
• Foster a product mindset and a research-to-production pipeline for data science solutions, ensuring scalability and usability
• Manage, mentor, and grow a high-performing team of data product managers, architects, engineers, and data scientists
• Define and monitor KPIs for both data products and data science initiatives, ensuring outcomes translate into tangible business impact
• Represent data and AI strategy at the executive level, influencing enterprise decisions and advocating for innovation
• Additional tasks may be assigned

• 12+ years of experience in data leadership roles, including data product management, data platforms, and data science
• Proven track record of building and scaling data products and machine learning/AI solutions in large, complex organizations
• Strong expertise in modern data and AI/ML architectures, including cloud platforms (AWS, GCP, or Azure), data lakes/warehouses, and governance frameworks
• Exceptional executive communication and stakeholder management skills, with the ability to influence across business and technology functions
• Demonstrated success in leading cross-functional teams spanning data science, engineering, and product management