Product Manager (Data)

TL;DR

Product Manager (Data): Supporting the product lifecycle focusing on the discovery, definition, and delivery of a suite of data products with an accent on stakeholder collaboration, agile requirement formalization, and roadmap development. Focus on analyzing business needs, managing product backlogs, and ensuring successful end-to-end delivery within a data-driven environment.

Location: London, UK (Hybrid role requiring weekly time in the office)

Salary: £53,629–£67,036

Company

hirify.global is a global non-profit operating an independent environmental disclosure system to drive transparency and sustainability through data.

What you will do

• Develop and maintain the product roadmap aligned with organizational goals and objectives.
• Conduct discovery and market research to validate product changes with end users.
• Collaborate with stakeholders to analyze business needs and identify pain points.
• Create detailed user stories, wireframes, and process diagrams to formalize requirements.
• Translate business needs into clear technical specifications for engineering teams.
• Facilitate Agile ceremonies and manage the product backlog to ensure efficient delivery.

Requirements

• Proven experience as a Product Owner or in a similar role within a product-led organization.
• Demonstrated experience in embedding and applying Agile methodologies.
• Strong analytical and problem-solving skills with a data-driven mindset.
• Excellent communication and collaboration abilities across diverse internal and external stakeholders.
• Proven record of end-to-end delivery within budget and timeline constraints.
• Must be able to attend the office in London on a weekly basis.

Nice to have

• Interest or passion for the environmental and sustainability sector.

Culture & Benefits

• Contribution to a global mission-driven organization focused on environmental transparency.
• Emphasis on a respectful and inclusive workplace environment.
• Opportunities for professional development through performance conversations and knowledge sharing.
• Collaborative team environment working closely with data and engineering experts.