Cadastra

Analyst

• Responsável pela gestão avançada da plataforma Google Workspace em ambientes corporativos complexos.
• Atua na implementação de políticas de segurança, automação de processos administrativos via APIs e GAM, suporte de alto nível, administração de usuários e recursos, além de garantir conformidade com normas de governança e boas práticas de TI.
• Administrar e manter o ambiente Google Workspace (Admin Console, GAM, APIs) com foco em segurança, performance e escalabilidade;
• Automatizar tarefas administrativas por meio de GAM, Google Apps Script, APIs REST e integração com plataformas de orquestração (ex: n8n, Zapier, Make, etc.);
• Gerenciar estruturas organizacionais, grupos, unidades organizacionais (OUs), permissões, aliases, licenças e recursos compartilhados;
• Implementar e revisar políticas de segurança e compliance: MFA, DLP, context-aware access, alertas, gerenciamento de dispositivos, regras de auditoria, etc.;
• Monitorar e gerar relatórios de atividades (Drive, Gmail, Calendar, etc.) via Audit Logs e Google Admin Reports;
• Suportar times internos em dúvidas técnicas sobre Gmail, Drive, Calendar, Meet, Chat, Keep, Groups, Forms e demais aplicativos do Google Workspace;
• Participar da definição e implementação de estratégias de governança para o ambiente Google Workspace;
• Conduzir projetos de migração de tenants, fusões e aquisições, transição de licenciamento e expansão organizacional;
• Atuar em conjunto com áreas como Segurança da Informação, RH, Jurídico e Compliance para garantir políticas alinhadas ao negócio;
• Documentar políticas, processos e scripts utilizados na operação do ambiente;
• Treinar equipes técnicas e usuários finais quanto ao uso eficiente e seguro da plataforma.

Analista Sênior de Google Workspace

• Keep client and supplier contracts organized both electronically and physically, supporting the management of these documents and control reports;
• Support the Commercial team (clients), Purchasing team (suppliers) and other internal areas in contract negotiations, negotiating terms and maintaining version and status control for each negotiated contract;
• Prepare amendments, agreements and standard company documents;
• Monitor the entire workflow of new contracts, amendments and other documents in a dedicated tool, managing tasks according to demand;
• Support internal meetings and help improve existing area processes;
• Interpret clauses and reports, identifying potential legal and/or commercial risks;
• Maintain the corporate registration documents for the companies in the group;

Contracts Analyst Jr – Legal

Customer Success Manager

• Manage an integrated, multichannel operation within Salesforce Marketing Cloud
• Organize the data structure within the platform
• Develop strategies for acquisition, activation, engagement, and retention
• Manage, clean, and cluster the database
• Structure project management, client meetings, and presentation materials
• Develop deliverables and tasks using agile methodology
• Perform performance, conversion, and engagement analyses
• Create dashboards and produce recurring reports
• Develop automations, SQL queries, and build data extractions
• Create and build complex relationship journeys

Mid-level CRM Analyst – Marketing Cloud

• Manage an integrated, multichannel operation within Salesforce Marketing Cloud
• Organize the data structure within the platform
• Develop strategies for acquisition, activation, engagement, and retention
• Manage, clean, and cluster the database
• Structure project management, client meetings, and presentation materials
• Develop deliverables and handle requests using agile methodology
• Perform performance, conversion, and engagement analyses
• Create dashboards and produce recurring reports
• Design and build complex customer relationship/journey flows
• Develop automations, SQL queries, and build data extractions
• Conduct trainings and assist in the technical development of assistants

Senior CRM Analyst – Marketing Cloud

Data Scientist

• Work on building and implementing models focused on generating business value, actively collaborating with the team to refine hypotheses.
• Build and maintain pipelines for data extraction, transformation, and analysis, ensuring data integrity and availability.
• Perform data cleaning and preprocessing to ensure consistency for modeling.
• Apply statistical methods for data exploration, visualization, and interpretation to generate actionable insights for business stakeholders.
• Implement and tune machine learning algorithms and mathematical optimization models to solve assigned problems.
• Monitor the performance of deployed models, apply evaluation metrics, and propose continuous improvements.
• Document processes and present technical and business results in a structured manner to the team and stakeholders.
• Support the setup of pipelines for deploying models in cloud environments, ensuring scalability.

Data Scientist, Mid-level

Machine Learning Engineer

• Model Operationalization (MLOps): Work on deploying Machine Learning models, turning prototypes (notebooks) into scalable, production-ready products.
• Pipeline Construction: Develop and maintain automated training, validation and inference pipelines (batch and real-time).
• Code Quality: Refactor modeling code with a focus on performance, readability and software engineering best practices (unit testing, modularization).
• Monitoring: Implement model monitoring strategies in production (data drift, concept drift and API performance).
• Infrastructure: Manage and optimize compute resources in a cloud environment (GCP) for running ML jobs.
• Model Governance: Keep experiment tracking and model versioning (Model Registry) organized.
• Collaboration: Act as a technical bridge between Data Science and Data Engineering teams.

Machine Learning Engineer, Mid-level

• Manage Windows and Linux servers.
• Manage the Group's cloud infrastructure (AWS and GCP).
• Administer the Google Workspace environment (accounts, groups, security, policies, integrations, logs, and audits).
• Perform backup and recovery routines.
• Monitor infrastructure performance and availability.
• Support documentation and process automation.
• Support migration and environment modernization projects.
• Implement cloud solutions for new and legacy workloads.
• Automate resource provisioning.
• Manage networks, IAM, security policies, storage, and VMs.
• Ensure security, compliance, and best practices in cloud environments.
• Collaborate with security, development, and architecture teams.
• Support microservices architecture, ensuring scalability, resilience, and observability of environments.
• Maintain and evolve container environments (Docker, Kubernetes, GKE, EKS).