Dlocal
Dlocal

Sr Data Product Manager

productfull-timeWorldwide
SALARY
Not specified
WORK TYPE
remote
JOB TYPE
full-time
INDUSTRY
fintech
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About the role

Headquarters: Madrid (Remote) / Spain / Brazil (Remote) / Argentina (Remote) / Montevideo (Remote) Why should you join dLocal? dLocal enables the biggest companies in the world to collect payments in 40 countries in emerging markets. Global brands rely on us to increase conversion rates and simplify payment expansion effortlessly. As both a payments processor and a merchant of record where we operate, we make it possible for our merchants to make inroads into the world’s fastest-growing, emerging markets. By joining us you will be a part of an amazing global team that makes it all happen, in a flexible, remote-first dynamic culture with travel, health and learning benefits, among others. Being a part of dLocal means working with 1000+ teammates from 30+ different nationalities and developing an international career that impacts millions of people’s daily lives. We are builders, we never run from a challenge, we are customer-centric, and if this sounds like you, we know you will thrive in our team. What’s the opportunity? This role calls for a product manager with a strong ability to deliver solutions that align with customer needs, regulatory standards, and strategic business goals. The ideal candidate should have proven experience in financial or payments products and a strong background in product management, specifically in delivering scalable, secure and innovative products for the payments or financial services industry. What will I be doing? Co-create and align the Data team's product vision, strategy, and roadmap with overall company goals, collaborating closely with engineering. Lead collaboration with engineering and product teams to ensure successful delivery and adoption of your data products. Manage stakeholder relationships , translating business needs into actionable data solutions. Define and analyze success metrics to measure the impact and value of data products. Optimize the data product backlog , prioritizing initiatives based on business impact,
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