RD Saúde

• Você será responsável pela sustentação da plataforma de automação n8n em modelo self-hosted sobre a infraestrutura da Amazon Web Services, garantindo disponibilidade, segurança, performance e atualização do ambiente. • Também atuará na administração e operação do AWS EKS, realizando rotinas de manutenção, controle de versões, ajustes de capacidade e suporte às aplicações executadas no cluster. • Faz parte das suas atribuições o desenvolvimento, evolução e sustentação de pipelines de CI/CD, apoiando os times de ciência de dados na entrega contínua, padronização de esteiras e automação de deploys. • Será igualmente responsável pela implementação e manutenção de infraestrutura como código (IaC) utilizando Terraform, garantindo versionamento, reprodutibilidade e governança dos ambientes. • Por fim, atuará fortemente em troubleshooting em ambiente cloud, investigando incidentes, falhas de pipeline, problemas de rede, acesso, performance e integração entre serviços, participando ativamente da melhoria contínua da plataforma e da confiabilidade dos ambientes produtivos.

• Estruturar e documentar processos da área de Engenharia de Dados • Acompanhar demandas, entregas e rotinas operacionais • Definir, consolidar e monitorar indicadores e KPIs • Realizar consultas e análises em SQL para levantamento e validação de dados • Organizar informações e elaborar materiais executivos e apresentações para comunicação de indicadores, resultados e evolução das iniciativas • Conduzir ou apoiar reuniões de acompanhamento, ritos e status de indicadores • Apoiar a comunicação das entregas e resultados da Engenharia de Dados para liderança e áreas parceiras • Atuar em parceria com times técnicos e áreas interfaces para dar visibilidade às entregas e apoiar a evolução dos processos

• Develop and maintain web applications, ensuring high quality and scalability. • Define, design, and implement new features in systems, collaborating with cross-functional teams. • Analyze business requirements and propose technical solutions aligned with business needs. • Ensure code quality through automated tests, code reviews, and engineering best practices. • Participate in the full software lifecycle — analysis, architecture, development, testing, and deployment. • Develop and consume REST APIs, ensuring secure integration between systems. • Collaborate with agile squads, contributing to technical decisions and continuous improvements of products. • Monitor production systems and resolve incidents, ensuring application availability. • Document processes, architectures, and services to maintain compliance and audit standards. • Implement APIs using Java/Spring Boot. • Build modern user interfaces with React. • Strong knowledge of Oracle (procedures/packages/triggers). • Create integrations with legacy systems and interoperability platforms using REST or messaging. • Perform evolutionary and corrective maintenance on existing modules. • Ensure application security and compliance, following standards such as access control and auditing. • Familiarity with CI/CD pipelines. • Integrate systems with gateways, messaging, and API platforms (e.g., Sensedia, internal gateway, etc.). • Act as a technical reference for less experienced developers, mentoring and reviewing code. • Support the product team in the technical design of features, story refinement, and estimations. • Monitor application logs and metrics using tools like DataDog.

• Responsible for supporting and maintaining RD Saúde's digital channels; • Develop solutions to fix bugs and critical incidents in the digital environment; • Analyze opportunities and implement actions that improve performance of the digital channels; • Conduct investigations and propose improvements to the digital environment to increase customer satisfaction on digital platforms (NSS); • Carry out and propose improvement actions aligned with FinOps practices (cost reduction and optimization); • Take a leading role in crisis rooms for critical incidents, focusing on restoring impacted services quickly and with quality; • Monitor the performance of implemented solutions, identify bottlenecks and propose continuous improvements;

• Support the development of statistical and machine learning models, both supervised and unsupervised. • Prepare, clean, and transform datasets (ETL/ELT processes). • Perform exploratory data analysis (EDA) to identify patterns, trends, and opportunities for improvement. • Create dashboards and automated reports using Power BI, Python, or similar tools. • Participate in the development and maintenance of data pipelines in collaborative environments. • Document processes, code, analyses, and results to ensure traceability and knowledge sharing. • Collaborate with business teams to understand problems and translate needs into analytical solutions. • Contribute analyses and studies that support the company’s strategic decisions.