Senior Product Manager, Data

WHO ARE WE Cognism is the leading provider of European B2B data and sales intelligence. Ambitious businesses of every size use our platform to discover, connect, and engage with qualified decision-makers faster and close more deals. Headquartered in London with global offices, Cognism’s contact data and contextual signals are trusted by thousands of revenue teams to eliminate the guesswork from prospecting. The Opportunity Cognism has built one of the most trusted B2B datasets in Europe. As we turn that data into market-leading products, we need a product manager who can own data products end to end - from understanding what customers are trying to achieve, to shaping what we build, to making sure it lands and creates value. This is a strategic role, where your leverage comes from the quality of your product decisions and your ability to align others around them. You will own a set of data products, be accountable for their quality, and be the person who turns a customer problem into a clear, buildable product that people genuinely want to use. The starting point is always the customer: what problem they have, what they have tried, and what would change their workflow. What This Role Owns • The strategy for your product area - where it's headed, what to bet on, and how it ladders up to the wider product vision. • The data products in your area - what they are, who they serve, and how they earn their place in a customer's workflow. • The customer use cases behind those products - which segments benefit, in which workflows, and to what outcome. • The quality of the data assets you own - accuracy, coverage, freshness, and delivery reliability - and the judgement of what is good enough to put in front of customers. • The delivery roadmap for your products - what you build, in what order, and what you deliberately leave out. • Adoption and value - proving that what you ship solves the problem it was meant to, not just that it shipped. What This Role Will Do Data product ownership and delivery • Own the product development cycle for your data products, from discovery and validation through to launch, adoption, and iteration. • Define requirements, set priorities, and make clear scope calls - what a product should and should not do, and why. • Work closely with data engineering and data science to shape data assets that can be delivered at the highest quality - so customers can build on data they trust - across CRMs, APIs, and agentic systems. • Ground every product decision in a customer use case and a commercial outcome, not just technical capability. • Define the success metrics and KPIs for your products up front, then measure outcomes continuously - using the data to drive decisions and iterate. • Shape how your products are packaged and priced - working with commercial teams so the way data is offered matches how customers buy and where they see value. Customer understanding • Turn customer needs into clear data requirements that engineering and data teams can build against. • Validate that what you build creates value - decide up front how you will know a product is working, and test it with real customers. • Partner with Sales and Customer Success so customers realise the value of the data, and feed what you learn back into the product. Data quality and governance • Own the quality of the data assets in your area and set the standard customers can rely on. • Decide how to surface confidence, freshness, and match quality to customers where it affects trust and adoption. • Build GDPR compliance and data governance into the product from the start. • Put evaluation frameworks in place - specific to data products - to measure data quality objectively and improve it continuously, so you can prove the data me