Qualifications:

• A minimum of 10 years' progressive experience in a related field preferred
• 3+ years experience leading organizational teams
• Track record delivering data products, semantic / metric layers, or data platforms in production
• Strong grasp of data quality, governance, lineage, and certification practices
• Experience making cross-boundary data trustworthy where no single team owned it
• Business fluency - ties data reliability to revenue, cost, and decision quality
• Bachelor's Degree in Arts/Sciences (BA/BS)
• Up to 10% of the time Domestic Travel only

Certain states and localities require employers to post a reasonable estimate of salary range. A reasonable estimate of the current base pay range for this position is $165,600 to $207k annually. Actual salary will be based on a variety of factors, including shift, location, experience, skill set, performance, licensure and certification, and business needs. The range for this position in other geographic locations may differ. Certain positions may also be eligible for variable incentive compensation, such as bonuses or commissions, that is not included in the base pay.

The well-being of WWT employees is essential. So, when it comes to our benefits package, WWT has one of the best. We offer the following benefits to all full-time employees: Health and Wellbeing: Health, Dental, and

• Vision Care, Onsite Health Centers, Employee Assistance Program, Wellness program
• Financial Benefits: Competitive pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Tuition Reimbursement
• Paid Time Off: PTO and Sick Leave (starting at 20 days per year) & Holidays (10 per year), Parental Leave, Military Leave, Bereavement
• Additional Perks: Nursing Mothers Benefits, Voluntary Legal, Pet Insurance, Employee Discount Program

We strive to create an environment where all employees are empowered to succeed based on their skills, performance, and dedication. Our goal is to cultivate a culture of belonging that encourages innovation, collaboration, and respect for all team members, ensuring that WWT remains a great place to work for All!



Brief Summary:

As a part of the newly formed AI Transformation Office, you will lead the Data Reliability & AI Readiness pillar and, in partnership with IT, set WWT's enterprise AI data strategy. You are accountable for driving strategies to ensure accurate data, proper usage of data in AI projects, and techniques to minimize token expense when accessing and analyzing data, setting the trust standard for the AI Transformation Office's data products. In this role you will be part of an extended data team using both structured and unstructured data to coordinate the data organization on enterprise initiatives across the business, and you bring consistency, reliability, accuracy, efficiency and scalability to how WWT manages its data. You will partner across the IT and enterprise data teams, the AI Transformation Office engineering team, embedded analyst teams and the AI Center of Excellence to ensure the data behind WWT's AI is ready for production use.

Job Responsibilities

• Set and drive WWT's enterprise AI data strategy - the path to data that's trustworthy, AI-ready, and reusable - and bring consistency and clarity to WWT's data management policies.
• Translate internal AI and data wins into go-to-market value - turning what we prove inside WWT into reference stories, patterns, and offerings the business can take to customers.
• Coordinate across the data organization on enterprise initiatives - identifying and managing the key data sources, attributes, and cross-boundary joins they depend on.
• Own the certification standard and "catalog of trust" - what "certified" and "AI-ready" data mean at WWT, plus lineage, quality SLAs, and readiness scoring - in partnership with the AI and enterprise data teams.
• Drive enterprise initiatives that improve WWT's key operational data, partnering with IT and the teams that own it.
• Own the AI Transformation Office's data products - telemetry, dashboards, reporting, and AI-based reporting - and how AI-powered and agent-built reporting reaches end users as trusted, adopted tools.
• Lead a Product Owner and engineers who build the org's data products and the shared certification tooling.
• Partner with IT (data platform, identity), the AI engineering team, business teams, and the analytics teams that own their data - to deliver the trusted, AI-ready data behind AI solutions.
• Make data economics visible - steer consumers to certified, pre-staged products instead of rebuilding the same data themselves.