Data Product Manager

Role overview Translate a global strategy for buy-now-pay-later and digital payments into data products that support business decisions and growth across more than ten markets. This role connects commercial, product and technical teams, shaping analytics, predictive models and AI-enabled tools from initial requirements through delivery and adoption.

Responsibilities - Turn strategy into prioritized initiatives, epics, requirements and roadmaps for payment and lending data products. - Work with analytics, data engineering and data science teams to plan scalable capabilities across markets. - Coordinate with product and software engineering teams on workflows, data contracts and requirements for data-driven applications. - Lead planning activities such as roadmap reviews, backlog refinement, sprint planning and stakeholder discussions. - Align data roadmaps with customer-facing application plans and ensure stakeholders can use reliable metrics and insights. - Present releases, roadmap changes and results to commercial stakeholders, gathering feedback and explaining analytical findings in business terms. - Work with data governance partners to follow data standards and platform guidelines; use AI tools to support documentation and planning.

Requirements - Bachelor’s degree in engineering, computer science, information systems, data science, systems analysis or a related technical field. - Relevant experience in data products, analytics, data engineering, data science or a related technical area. - Experience translating business objectives into product requirements, roadmaps and data-led solutions. - Strong SQL skills and hands-on experience with a visualization tool such as Power BI or Tableau. - Understanding of analytics, KPI design, data storytelling and statistical concepts. - Experience with Agile product development and backlog management, plus strong stakeholder communication skills. - Fluent English; able to work across business and technical teams, prioritize amid ambiguity and build alignment.

Nice to have - Background in fintech, digital payments, lending or financial services data. - Knowledge of machine learning, feature engineering, model monitoring or MLOps. - Experience with Azure, Databricks or other cloud data platforms; relevant product, analytics or platform certifications. - Spanish proficiency.

Benefits and work setup Benefits listed include performance and attendance bonuses, pension, meal and transport allowances, health, dental and life insurance, childcare support, training resources, and education-related assistance. Some benefits are subject to program rules.