Senior Product Manager (Data)

• 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
• 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
• 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
• 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 meets the standard customers rely on
• Work with data sourcing teams to expand and strengthen the datasets behind your products - deciding what to source, build, or partner for
• Act as the primary point of contact for your product area across Engineering, Data Science, Sales, Customer Success, Commercial, and Compliance — translating between technical and commercial language as needed
• Manage dependencies with product peers who own adjacent surfaces; where priorities conflict, resolve disagreements directly and drive to a decision without escalation unless necessary
• Keep senior stakeholders (e.g. leadership, commercial leads) informed of roadmap trade-offs and progress, proactively surfacing risks before they become blockers
• Build trust with customer-facing teams (Sales, CS) so they can represent your product accurately and feed real customer signal back into your roadmap
• Where a decision affects multiple teams, take ownership of driving alignment — running the discussion, not just attending it
• Keep a current view of the B2B data market - how it is evolving, who the key players are, and what customers are choosing and why
• Use that view to sharpen your products and spot where Cognism’s data can create differentiated value

Benefits

• Generou…