Senior Product Manager, Data

Overview

Join Cognism to own data products end to end, turning customer problems into buildable offerings that drive value. You’ll steer strategy, define data-based solutions, and ensure high-quality assets with measurable impact. Collaborate across data, engineering, and commercial teams to align product decisions with customer outcomes. This role offers a chance to shape market-leading data products in a fast-growing environment.

Responsibilities

• Own the end-to-end product development cycle for data products from discovery to launch and iteration
• Define requirements, priorities, and scope decisions to constrain what the product should and should not do
• Collaborate with data engineering and data science to deliver high-quality data assets across CRMs, APIs, and agentic systems
• Anchor product decisions in customer use cases and commercial outcomes
• Set up success metrics and KPIs upfront and continuously measure outcomes to inform iterations
• Shape packaging and pricing in collaboration with commercial teams to align with how customers buy and perceive value
• Convert customer needs into clear data requirements for engineering and data teams
• Validate value creation with customers and gather feedback to drive product direction
• Own data quality and governance, ensuring data accuracy, freshness, coverage, and trust
• Work with compliance and security experts to build governance and security in by design
• Manage cross-functional dependencies and keep senior stakeholders informed of roadmap trade-offs and risks
• Maintain market awareness to sharpen products and differentiate Cognism’s data offerings
• Build alignment across Engineering, Data Science, Sales, CS, Commercial, and Compliance

Key requirements

• 5+ years in product roles with direct ownership of data products or data-driven features in B2B SaaS or tech
• Ability to define and own data use cases mapping segments, workflows, and outcomes to a product direction
• Experience setting product strategy for an owned area and making prioritization decisions
• Direct experience treating data as a product including defining offerings and market impact
• Commercially minded with understanding of customer buying drivers and value
• Track record of customer discovery through interviews, research, or feedback loops
• Technical fluency to work credibly with engineering and data teams
• Hands-on experience building ML-driven data features including model enrichment and signals
• Strong cross-functional collaboration with product, engineering, and commercial teams
• Clear communication to simplify complex data propositions for customers
• Capacity to work with compliance and security teams to embed governance by design

• cross-functional collaboration
• customer-centric mindset
• clear communication
• ML-driven data features understanding of models, enrichment, and signals
• data governance and GDPR compliance
• data quality metrics and evaluation frameworks

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