What are the responsibilities and job description for the Vice President, Data Architecture and Engineering (Remote) position at KOHLS?
About the Role
The VP, Data Architecture and Engineering is accountable for the vision, strategy, and execution of the enterprise data platform and engineering capabilities that enable business growth, operational efficiency, and customer centric innovation. This leader partners closely with business and technology teams to elevate data into a durable and scalable enterprise asset. In alignment with the VP of A.I and Transformation, who defines enterprise A.I strategy and prioritizes business use cases, this role owns the data architecture, platforms, and engineering foundations required to operationalize, scale, and reliably run A.I solutions in production across the enterprise.
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 strategy at the executive level, influencing enterprise decisions and advocating for innovation
Additional tasks may be assigned
What Skills You Have
Required
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