
Analytics Engineer Specialist at RecargaPay. Come and impact millions of Brazilians!!. Want to make a difference in the lives of millions of Brazilians? . At RecargaPay, we create accessible and innovative financial solutions that transform the way people interact with money. Be part of this impactful and innovative journey, connecting people with opportunities that truly make a difference in their daily lives.. Our purpose is to deliver the best mobile payment experience for Brazilians, addressing real-world challenges with smart solutions like Pix Parcelado, while staying attentive to market trends and our customers' needs. Here, we value collaboration, ownership, and a relentless pursuit of results, delivering excellence in every interaction.. If you’re looking to join a dynamic environment that challenges the status quo and puts people at the center of decision-making, RecargaPay is the perfect place for you to grow, co-create, and make a difference!. Responsibilities. We are seeking a highly skilled and business-driven . Analytics Engineer Specialist. to join our Data team at RecargaPay. In this role, you will lead the design and implementation of scalable, high-performance analytical data models and solutions that power strategic decision-making across the organization. You’ll collaborate cross-functionally with Product, Engineering, and Business stakeholders to ensure our data infrastructure not only supports but drives business impact, data democratization, and innovation.. . 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.. . . Strong experience with SQL and PySpark for analytical development and scalable data processing. . . Proven ability to design and build analytical views and reusable data assets, aligned with business logic and performance standards. . . Proficiency in visualization tools, preferably Qlik Sense and Tableau, or equivalent platforms (e.g., Power BI, Looker). . . Hands-on experience with Databricks, including the development of business-oriented data marts and analytical models. . . Familiarity with dbt, Git, and collaborative documentation tools (e.g., Confluence, Notion, Markdown-based wikis). . . Ability to translate business requirements into governed, maintainable, and scalable analytical solutions. . . Lead methodological definitions for KPIs, metric standardization, and modeling conventions across the organization. . . Design cross-domain analytical solutions that are interoperable and scalable beyond individual products or squads. . . Represent the Analytics Engineering discipline in data governance, data quality, and data architecture committees, contributing to enterprise-level guidelines. . . Collaborate with other Analytics Engineers, actively sharing frameworks, best practices, and reusable components within the analytics chapter. . . Contribute to strategic decisions regarding the evolution of the analytical platform, including naming conventions, data catalog structure, semantic layers, and observability tooling.. . Company Location: Brazil.