Leega

Product Manager

• Act as the primary point of contact for business areas, collecting and analyzing requirements for new AI, Data, and Automation solutions.
• Conduct interviews and workshops with business teams to map processes, identify pain points, and uncover optimization opportunities.
• Translate business needs and challenges into clear, well-documented technical and functional specifications for specialist teams (data scientists, AI engineers, developers).
• Validate the technical feasibility of proposals together with the specialist team, ensuring alignment between business expectations and execution capabilities.
• Collaborate on prioritizing requests and designing the backlog for AI and Automation projects.
• Monitor the development and implementation of solutions, ensuring that outcomes align with the initial requirements.
• Communicate project progress and results effectively to stakeholders at different levels, both technical and business.

Senior Product Owner – Focus on AI and Automation

Data Engineer

• Engenheiro Devops Sênior + Pipeline de Dados
• Desenvolvimento de pipeline de dados para o Data Lake;
• Manutenção dos processos para correção de falhas/erros;
• Implementação de melhorias;
• Atuará no contexto de FastData, implementará os consumers como microserviços no EKS, enriquecerá os eventos com dados da plataforma e integrará do Adobe Analytics.
• Atuar como parte da equipe ágil;
• Colaborar com outros membros da equipe, Engenheiros, PO, QA, Designers, Scrum Master, Funcional e Tech Lead para resolver os desafios existentes;
• Desenvolver, implantar e operar aplicações na cultura DevOps;
• Modelagem de Dados Relacional e Dimensional.

Engenheiro DataOps Sênior – AWS

Backend Engineer

• Develop, maintain and enhance high-performance microservices.
• Work on resolving Level 2 and Level 3 incidents, performing complex diagnostics involving code, cloud infrastructure and acquiring business rules.
• Ensure the integrity of integrations between Payware platforms and the company's other systems.
• Propose continuous architectural improvements to reduce incidents, increase scalability and optimize performance in AWS and on-premises environments.
• Document technical flows, integrations and business rules, promoting knowledge sharing across the team.
• Provide technical support and mentorship to less experienced colleagues through coaching and knowledge sharing.

Senior Java Developer – Acquiring and Payments

Data Analyst

• Requirements Gathering and Documentation: Translate business needs into functional requirements for data projects, focusing on mapping business metrics and customer master data integrity rules.
• Master Data Cleansing Strategy: Diagnose the current state of databases (data cleaning) and propose conceptual solutions to improve record quality without relying on pre-existing tools at the bank.
• Bureau Mapping: Identify and evaluate external databases and market bureaus for procurement, aiming to enrich and validate customer/master data.
• Bridge between Business and IT: Collaborate with stakeholders and developers to ensure technical solutions accurately reflect business rules and established governance standards.
• Modeling and Governance: Create and maintain conceptual and logical data models, ensuring documentation of metrics and quality processes remains up to date.
• Validation and Quality: Test and validate implemented solutions to ensure metrics are accurate and that data cleansing processes operate as intended.
• Governance Gatekeeper: Act as a facilitator with the Data Governance area, applying necessary standards to ensure speed and compliance in projects.

Functional Data Analyst

Full-stack Engineer

• Responsible for designing, proposing, developing, and delivering technical solutions for systems and integrations
• Work across all stages of development for projects requested by business stakeholders to the IT department
• Be part of a multidisciplinary team and take responsibility for the full software development lifecycle
• Participate in software development projects, proposing, developing, and delivering technical solutions that are secure and scalable
• Have experience working as a Full-Stack developer
• Familiarity with development best practices
• Collaborate with other team members to resolve existing challenges
• Write, code, and test software for the systems being developed
• Identify and fix bugs
• Maintain existing systems

Software Engineer – Mid-level

• Direcionamento Arquitetural: Definir e sustentar a arquitetura de microsserviços em Java
• Governança e Qualidade: Estabelecer padrões de desenvolvimento e conduzir revisões de código
• Mentoria e Multiplicação: Orientar o time na resolução de problemas complexos
• Estratégia de Testes e Automação: Liderar a estratégia de testes automatizados
• Interface Técnica: Atuar como ponte entre as necessidades de produto e a viabilidade técnica
• Observabilidade e Evolução: Monitorar a saúde dos sistemas e propor melhorias contínuas

Tech Lead – Java

Data Scientist

• 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).

Cientista de Dados Pleno – Foco em IA Generativa, GenAI

• 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).

Senior Data Scientist – Focus on Generative AI, GenAI

DevOps Engineer

• 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.

Senior SRE, Databricks

• Load/Pipeline Analysis and Planning:
• Evaluate the data warehouse architecture and requirements.
• Map data, transformations and processes to GCP services (Cloud Storage, BigQuery, Dataproc).
• Define the data migration strategy (full load, incremental, CDC).
• Develop a data architecture plan on GCP.
• Data Design and Modeling on GCP:
• Design table schemas in BigQuery considering performance, cost and scalability.
• Define partitioning and clustering strategies for BigQuery.
• Model data zones in Cloud Storage (Bronze, Silver and Gold).
• ELT/ETL Pipeline Development:
• Create data transformation routines using Dataproc (Spark) or Dataflow to load data into BigQuery.
• Translate business logic and existing transformations into GCP.
• Implement data validation and quality mechanisms.
• Performance and Cost Optimization:
• Optimize BigQuery queries to reduce costs and improve performance.
• Tune and optimize Spark jobs on Dataproc.
• Monitor and optimize GCP resource usage to control costs.
• Data Security and Governance:
• Implement and ensure data security in transit and at rest.
• Define and enforce IAM policies to control access to data and resources.
• Ensure compliance with data governance policies.
• Monitoring and Support:
• Troubleshoot performance and functionality issues of data pipelines and GCP resources.
• Documentation:
• Document the architecture, data pipelines, data models and operational procedures.
• Communication:
• Communicate effectively with team members, stakeholders and other company areas.
• Ensure clear communication between architecture definitions and software components, and oversee the evolution and quality of the team's development.
• Jira / Agile Methodologies:
• Be familiar with agile methodologies, their rituals, and be proficient with Jira.

Mid-Level Data Engineer – GCP, DBT

• 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.

Data Engineer – Senior (GCP)

• 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.

Data Engineer – Mid-level

• 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.

Senior Data Engineer – GCP, BigQuery, Dataflow

Analytics Engineer

• Work directly within tribes requiring the development of data pipelines and new dashboards.
• Strong experience as an Analytics Engineer, BI Engineer, or in a similar role.
• Minimum proven experience: 5 to 6 years (required).
• Advanced SQL: deep knowledge of schema design, query optimization, and dimensional/relational modeling.
• Advanced experience with DBT: professional use in building, testing, and documenting data transformation pipelines.
• Experience with Airflow: building, maintaining, and orchestrating complex data pipelines.
• Google Cloud Platform (GCP):
• Expertise in BigQuery: in-depth knowledge of performance tuning, cost management, and advanced platform features.
• Familiarity with other GCP data services (e.g., Google Cloud Storage).
• Experience with BI/visualization platforms: proficiency in developing dashboards on the Looker Platform.

Senior Analytics Engineer

Analyst

• Atuar na análise crítica e evolução de processos corporativos, com foco em simplificação e eficiência.
• Após a fase inicial, assumir a atuação como PMO do projeto, apoiando a coordenação, governança e execução das atividades.
• Aprofundar o entendimento dos processos atuais (AS-IS), identificando o que ainda faz sentido no cenário futuro
• Avaliar redundâncias, complexidades desnecessárias e pontos de fricção
• Propor simplificações e melhorias orientadas à eficiência e experiência do usuário
• Desenhar fluxos futuros (TO-BE), considerando a integração entre sistemas e áreas
• Garantir a fluidez dos processos transversais entre diferentes áreas
• Conduzir discussões com áreas de negócio para validação e refinamento dos fluxos
• Traduzir necessidades de negócio em processos claros e estruturados
• Documentar processos e recomendações de forma objetiva e organizada
• Apoiar a governança do projeto (cronograma, status, riscos e dependências)
• Acompanhar entregas, marcos e evolução das iniciativas
• Facilitar a comunicação entre áreas de negócio e times técnicos
• Atuar na gestão de riscos, impedimentos e planos de mitigação