Steve Pimblett is Chief Data Officer at Rightmove, where he leads the organisation’s data and AI strategy with a focus on translating insight into measurable commercial impact.
He brings more than 20 years’ experience building data and analytics capabilities across a range of digital and consumer businesses. Steve began his career with a strong foundation in applied statistics and analytics in his home city of Liverpool, before progressing into senior leadership roles where data became a core strategic asset rather than a support function.
Across organisations including Moneysupermarket, Betsson, Wejo, The Very Group, and Rightmove, Steve has frequently been appointed as the first Chief Data Officer. In these roles, he has been responsible for establishing data strategy, platforms, operating models and teams from the ground up. His work has included commercialising large-scale consumer and industry data assets, building global cloud and streaming platforms, and embedding AI and advanced analytics into customer and partner journeys.
Steve has led data transformations at every scale, from high-growth start-ups to FTSE 100 organisations. This breadth of experience has shaped a pragmatic view of data leadership: sustainable advantage comes from tight alignment between data, business strategy, product development and organisational culture. He is known for balancing innovation with trust, security and regulatory compliance.
At Rightmove, Steve’s focus is on execution, turning ambition into effective operating models, embedding responsible AI practices, and unlocking long-term value from data while maintaining the confidence of customers, partners and regulators.
As a data and AI leader, which traits and skills do you think matter most, and which of those have been most influential for you in your current position?
“Effective data and AI leadership comes down to a small number of critical traits: commercial clarity, execution discipline, trust leadership, and the ability to influence at scale.
“The most important skill is connecting data and AI to real business outcomes. Technical depth matters, but impact comes from translating complexity into decisions that drive growth, efficiency and customer value.
“Strong leaders also think in operating models: moving from experimentation to repeatable execution through clear ownership, governance, and prioritisation. As AI becomes more pervasive, trust is non-negotiable: privacy, security, regulatory compliance and ethical AI must be embedded by design, not retrofitted later.
“Finally, clear communication and change leadership are essential to align senior stakeholders and shift organisational behaviour.
“In my own career, commercial focus and execution have been the most influential. Building first-time CDO functions taught me that strategy only counts when it lands in products, processes and P&Ls. Working in regulated environments reinforced that trust isn’t a brake on innovation, it’s what allows AI to scale and endure.”
Reflecting on your career, what is one non-traditional piece of advice (outside of technical skills) you would give to an aspiring data or AI leader aiming for the C-suite?
“One non-traditional piece of advice is to learn to lead ambiguity, not certainty.
“At C-suite level, data and AI leaders are valued less for having the ‘right answer’ and more for their ability to frame trade-offs, absorb complexity, and create confidence when the data is incomplete. The hardest decisions sit at the intersection of growth, risk, regulation, ethics, and culture where tension is inevitable and certainty is rare.
“In my career, the ability to stay calm in ambiguity, align diverse stakeholders, and keep momentum has mattered far more than technical mastery. Boards need data and AI expertise, but what they really value is a leader they trust to turn uncertainty into clear direction and tangible business value.”
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