Leega

• Atuar como referência técnica em projetos de dados e automação • Traduzir demandas de negócio em soluções técnicas (modelagem, automações, pipelines) • Projetar, estruturar e documentar soluções de ponta a ponta • Desenvolver automações e otimizações de processos • Antecipar melhorias com base no entendimento do negócio • Comunicar resultados para públicos técnicos e não técnicos • Colaborar com times multidisciplinares (negócio, engenharia, arquitetura)

• Desenvolver e aprimorar modelos de Machine Learning e Inteligência Artificial Generativa para a geração automática de conteúdos de marketing. • Dar sustentação, evolução e continuidade ao desenvolvimento do projeto como um todo, garantindo a escalabilidade da arquitetura de agentes de GenAI. • Trabalhar na estruturação, adaptação e entrega dos conteúdos gerados para diferentes interfaces (Web, App, Mobile).

• Develop and enhance Machine Learning and Generative AI models for the automatic generation of marketing content. • Provide support, evolution, and continuity for the overall project development, ensuring the scalability of the GenAI agent architecture. • Work on structuring, adapting, and delivering generated content for different interfaces (Web, App, Mobile).

• Provide technical leadership for the data team, acting as a reference for architecture and best practices • Evaluate, propose and evolve data architecture solutions (batch and streaming) • Translate business needs into efficient, scalable technical solutions • Work closely with business areas, especially in CRM and Martech contexts • Desirable experience with Salesforce products (Sales Cloud, Marketing Cloud, Service Cloud, integrations, and data models) • Ensure data quality, governance, and reliability • Support strategic decisions related to data platforms and tooling • Promote engineering best practices (modularization, testing, observability, etc.) • Mentor and develop the technical skills of the team

• Conduct assessments with clients to understand business challenges, processes, pain points, and opportunities for applying Artificial Intelligence. • Act in a consultative capacity, questioning existing processes and proposing new ways of working supported by AI. • Identify, design, and prioritize AI use cases focused on delivering business value. • Design, develop, and deploy AI solutions using LLMs, intelligent agents, RAG, automations, and other modern architectures. • Develop applications using AI as an accelerator for the development cycle (AI-assisted development). • Create AI agents capable of executing tasks, integrating systems, orchestrating flows, and supporting corporate processes. • Integrate AI solutions with APIs, legacy systems, cloud platforms, and enterprise tools. • Collaborate with architects, infrastructure specialists, DevOps, and development teams to ensure scalability, security, and governance of solutions. • Participate in defining modern application architectures with a focus on AI. • Build proofs of concept (PoCs), MVPs, and production-ready solutions. • Support clients in adopting best practices for responsible AI, security, governance, and cost optimization. • Keep up with the evolution of the Generative AI ecosystem, continuously evaluating new tools, models, and frameworks. • Share knowledge through workshops, technical demonstrations, and team training.

• Desenvolver soluções modernas de dados e integrar pipelines com aplicações externas • Apoiar iniciativas de IA e Machine Learning • Construir e evoluir uma plataforma de dados escalável, voltada para analytics avançado e aplicações inteligentes

• Develop automated pipelines to ingest 100% of the data from the Risk tool into GCP. • Design and provide governed views in the Analytics layer (BigQuery), ensuring data integrity and quality for downstream consumption. • Implement metrics based on complex SQL logic and business rules. • Develop semantic indicators using LLMs via GCP (Vertex AI) for categorization and analysis of unstructured data. • Work directly with the software engineering team to ensure the solution aligns with the company's architecture and security standards.

• Create, maintain and evolve Terraform modules for provisioning the data infrastructure. • Manage state management, workspaces and infrastructure versioning best practices. • Ensure reproducible, auditable and traceable infrastructure via code. • Provision and manage networks (VPCs, subnets, firewall rules) following security best practices. • Configure IAM: roles, policies and service accounts with the principle of least privilege. • Manage Google Cloud Storage (GCS) as the storage layer for the data platform. • Ensure compliance with cloud security and governance policies. • Provision and configure Databricks workspaces via Terraform/IaC. • Manage clusters, jobs, notebooks and permissions on the platform. • Integrate Databricks with GCP infrastructure (service accounts, VPC, GCS, IAM). • Build and maintain CI/CD pipelines for infrastructure (GitHub Actions or similar). • Apply GitOps practices: all infrastructure changes via Pull Request with review and automated validation. • Ensure secure and auditable deployment across multiple environments (dev/staging/prod). • Implement secrets and credential management following best practices (Secret Manager, Vault, etc.). • Automate and standardize environments to ensure consistency and eliminate manual configuration. • Support the data team with reliable, self-service infrastructure.

• Design and build scalable, resilient data analytics solutions on GCP. • Propose and implement architectural improvements. • Elicit requirements from business areas and document them. • Familiarity with agile methodologies. • Align the corporate IT environment with business needs, standards, and industry best practices. • Be able to incorporate a data-driven culture into daily work. • Ability to work collaboratively with empathy, to listen and be heard, and to communicate effectively.

• Automate processes for data analysis. • Identify key market variations. • Develop hypotheses in collaboration with business stakeholders. • Publish analyses and dashboards for all levels of the company. • Technically lead a team focused on creating processes and monitoring metrics.