Job Description: If you strive to make a difference and leverage data, technology, and innovation to simplify the healthcare sector, our Technology, Data, Products, and Design teams are ready to welcome you. To transform healthcare, we require: * A completed undergraduate degree in fields such as Computer Science, Engineering, Information Systems, Mathematics, Statistics, or related disciplines; * Solid experience with SQL, focusing on data modeling and query optimization for Data Warehouse/Lakehouse environments; * Practical experience in cloud environments, with proficiency in Google BigQuery; * Experience with data orchestration and modeling tools such as dbt (Data Build Tool), including application of software engineering principles (testing, documentation, modularity); * Strong knowledge of code versioning using Git; * Experience with Business Intelligence (BI) tools: Power BI and Looker; * Preferred: Python knowledge for automation and data manipulation; * Preferred: Experience with data cataloging and governance tools such as OpenMetadata; * Preferred: Familiarity with Tabular Editor (if applicable to your tech stack); * Behavioral Competencies: * Strong analytical thinking and logical reasoning; * Excellent interpersonal skills and teamwork; * Strong written and verbal communication, along with active listening; * Ability to plan, organize, and self-manage. About the Role: * Design, develop, and maintain optimized data models in the refined layer of our Data Warehouse/Lakehouse, aiming for high performance and ease of consumption by Business Intelligence tools and other applications; * Perform extraction, transformation, and loading (ETL/ELT) of data from diverse sources, ensuring data quality, consistency, and integrity; * Proactively collaborate with business teams, data scientists, and analysts to understand data requirements and translate them into robust, scalable solutions; * Support the development and optimization of dashboards in BI tools, ensuring visualizations deliver clear, actionable insights for business areas; * Actively contribute to identifying opportunities to enhance data infrastructure and Analytics Engineering processes. 2512070202191667066