VP/AVP, Specialist, Marketing Data Product Owner, Group Marketing & Communications

Role Overview

The Marketing Data Product Owner will define, build and scale the data capabilities required to support marketing across audience management, campaign activation, performance analytics and measurement.

What You Will Do

Translate business needs into clear product requirements, lead delivery with engineering and analytics teams, validate solutions through testing, and drive adoption and continuous improvement across teams and markets.

Why It Might Be a Fit

The role requires strong product judgement, stakeholder management and executive communication skills, with the ability to align Marketing, Data and Technology teams and make clear prioritisation trade-offs.

Requirements

• 8–12 years of experience in data product management, customer data, marketing analytics, CRM, segmentation, MarTech or a related field.
• Demonstrated ownership of data products from product strategy and discovery through requirements, delivery, launch, adoption and continuous improvement.
• Experience defining audience, customer or prospect data products, including segment logic, audience composition, taxonomy, lifecycle and activation requirements.
• Practical understanding of marketing measurement, paid media performance reporting, attribution and Marketing Mix Modelling.
• Strong SQL and data fluency, with the ability to understand data models, identity resolution, data quality, lineage and batch or real-time integration patterns.
• Experience working with customer data platforms, audience platforms, cloud data platforms, data warehouses, APIs and business intelligence tools such as Power BI or Tableau.
• Experience leading user acceptance testing, validating data products against business scenarios and managing release readiness with engineering and business teams.
• Strong product judgement, stakeholder management and executive communication skills, with the ability to align Marketing, Data and Technology teams and make clear prioritisation trade-offs.

Tagged as: Power BI, SQL, Tableau