Vice President, Data Architecture, Engineering & AI
Kohl's · United States
Skills in this posting
Extracted from the posting text by the instrument — the demand side, read literally.
The posting
Role Specific Information Job Description 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
Essential Functions The requirements listed below are representative of functions you will be required to perform, however you may be required to perform additional functions. Kohl’s may revise this job description from time to time. To perform this job successfully, you must be able to perform each essential function satisfactorily. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions, absent undue hardship.
Ability to perform the accountabilities listed in the “What You’ll Do” Section
Ability to maintain prompt and regular attendance as set by the company
Ability to work at least 8 hours per day, occasionally longer when necessary to meet business needs, 5 days per week
Ability to comply with dress code requirements
Ability to learn and comply with all company policies, procedures, standards and guidelines
Ability to give direction and receive, understand and proactively respond to direction from leadership and other company personnel
Ability to work as part of a team and interact effectively and appropriately with others
Ability to maintain composure and work in a fast paced environment while accomplishing multiple tasks within established timeframes
Ability to satisfactorily complete company training programs
Perform work in accordance with the Physical/Cognitive Requirements section
Physical/Cognitive Requirements
Ability to use a personal computer for tasks such as communicating, preparing reports, etc.
Ability to plan, prioritize and monitor activities across business units
Ability to complete or oversee the completion of assigned projects in a timely manner
Ability to comply with health and safety standards
Originally posted on Himalayas
Excerpt from the original listing. The full, current text lives at the source. Read and apply there →
The PivotHop read
- What a data architect actually earnsmedian, seniority, by country
- Data Architect career changes, measuredevery measured route out
- Data Engineer → Data Architect90% readiness
- All open data architect rolesthe full board
Where these skills also reach
Adjacent occupations measured from the same postings — readiness is what a data architect’s profile already covers.
- 250 open solutions architect roles55% readiness from data architect
- 250 open data engineer roles48% readiness from data architect
- 184 open data analyst roles41% readiness from data architect
- 23 open database administrator roles40% readiness from data architect
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