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Strategic Data Architect

2 semanas atrás


São Paulo, São Paulo, Brasil beBeeData Tempo inteiro US$3.500.000 - US$5.000.000
Unlock the Power of Data

We're on a mission to deliver exceptional payment experiences for consumers and businesses by building a powerful digital ecosystem.

We serve millions of users, process significant volumes annually, and operate our own credit business. As an AI-first, 100% remote team, we scale in the rapidly changing financial market.

Our goal is to deliver best-in-class payment experiences in Brazil for people and businesses alike.

We value autonomy, ownership, and a bias for action. We're looking for individuals who are curious, hands-on, and driven by impact - who want to solve real problems, work with strong teams, and rethink what's possible.

Join us if you're ready to do your best work, at scale, with purpose.

Key Responsibilities

As a highly skilled Analytics Engineer Specialist, you will lead the design and implementation of scalable, high-performance analytical data models and solutions that drive strategic decision-making across the organization.

  • Lead the modeling and architecture of analytical data, focusing on performance, scalability, and adherence to market best practices.
  • Design and oversee the development of strategic dashboards and analytical layers that serve multiple areas and levels of the organization.
  • Act as a data advisor for key departments, supporting the definition of KPIs, advanced analyses, and data-driven decision-making frameworks.
  • Ensure standardization, governance, and version control of implemented analytical solutions, integrating them with existing data pipelines.
  • Lead initiatives for analytical automation and data democratization, promoting the use of self-service tools and internal training.
  • Collaborate with Data Engineering, Product, and Technology teams to build solutions that connect data to digital products, processes, and business strategies. Mentor Analytics professionals, fostering technical development, methodological consistency, and data storytelling best practices.
  • Monitor and implement new trends and technologies in data analysis, contributing to the continuous evolution of the field.