Leega

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

Analista de Processos – PMO

Data Engineer

• Support and enhancement of processes in a GCP environment;
• Development in Python;
• Data ingestion with automated pipelines;
• Processing and analysis of large volumes of data;
• Simplification aimed at efficiency driven by customer needs;
• Data- and fact-driven decision making with ownership;
• Continuous, shared learning;
• Create/maintain data flows and datasets;
• Develop/model databases for dashboards and reports;
• Document developed processes;
• Gather and clarify database/variable requirements with the business.

Senior Data Engineer, dbt, GCP

• Work in a hands-on capacity
• Contribute to structural definitions
• Collaborate with internal teams
• Provide critical insights and propose improvements
• Support the advancement of data quality maturity

Senior Data Quality Analyst

• Design and implement the dbt platform architecture on Databricks (Unity Catalog, medallion layers: bronze/silver/gold).
• Structure the dbt project: modeling standards, naming conventions, layers (staging/intermediate/marts), macros, tests, and documentation.
• Build CI/CD pipelines for dbt (validation, build, tests, deploy per environment — dev/staging/prod).
• Automate provisioning and operations using IaC (Terraform) and DevOps practices.
• Optimize cost and performance (clusters, SQL Warehouses, Photon, partitioning, incremental processing).
• Define data governance and security (Unity Catalog, access control, masking of sensitive data).
• Mentor the team on analytical engineering best practices and review code (PRs).

Senior Data Engineer – Databricks, DBT

• Leega is a company dedicated to providing efficient, innovative service to its clients — and our greatest asset is our people. Our culture is inspiring and our values guide daily life: ethics and transparency, commitment to quality, teamwork, economic, social and environmental responsibility, human relations, and credibility. We seek innovative professionals who are motivated by challenges and focused on results. If you are looking for a dynamic, supportive company that invests in employees through continuous training, Leega is the place for you! >> LEEGA IS FOR EVERYONE — we will be very happy to have you on our team. Come be part of our story and help build our future. Register for our openings now!

Senior Data Architect – Google Cloud Platform, Databricks

Project Manager

• Lead projects end-to-end, from planning through closure, using waterfall and agile cycles according to the nature of each deliverable
• Manage scope, schedule, budget, and risks, ensuring alignment with business objectives
• Facilitate agile ceremonies (planning, review, retrospective, daily) and steering committee meetings on structured projects
• Build and maintain detailed project plans (Work Breakdown Structure - WBS, project schedule, Gantt chart) when applicable
• Serve as the primary point of contact between technical teams, business areas, and executive stakeholders
• Produce status reports, executive presentations, and project documentation with clarity and consistency
• Identify and escalate impediments, managing dependencies between teams and vendors
• Contribute to the maturity of PMO practices by proposing process improvements and templates

Risk

• Ensure Livelo's data volume is a secure, reliable, and democratized asset.
• Design, implement and evolve Data Governance policies, rules, and standards.
• Structure and maintain the Data Catalog and Data Lineage.
• Define and monitor metrics, KPIs, and Data Quality rules.
• Ensure compliance with LGPD guidelines and information security policies.
• Act as a facilitator and bridge between Data Engineering, Architecture teams, and Business stakeholders.

Data Governance Analyst – Mid-level

Data Scientist

• Must be able to lead an entire project with minimal supervision, designing and building mathematical/statistical solutions according to business requirements.
• From the initial meeting, define the project scope with the business area, translating requirements into programmatic statistical models.
• Analyze timelines and trade-offs between techniques and business needs; implement all project stages (data collection and analysis, formatting for model ingestion, modeling, and generation of usable outputs).
• Must also be able to guide and teach any part of the machine learning project lifecycle to less experienced team members.
• Liaise with the business area regarding any needs during the project.
• Development of transactional chatbot models.
• Create AI models to apply rules for identifying transactional fraud.
• Correlate datasets.
• Create dashboards to visualize the key established metrics.
• Document the development technically.

Senior Data Scientist, Chatbot, AI

QA Engineer

• Senior professional with a strong analytical profile.
• Good communication skills with both business and IT teams.
• Ability to understand business rules.
• Experience in functional, integration, and regression testing.
• Validation of business rules with end users.
• API testing (Postman/Swagger or similar).
• Oracle database (PL/SQL – queries and validations).
• .NET systems.
• Tools such as Jira and Zephyr.

Senior QA Analyst

Backend Engineer

• Software development using Python.
• Creation and maintenance of automated tests.
• Collaboration with teams on CI/CD processes.
• Deployment and support of cloud applications.

Senior Python Developer

Machine Learning Engineer

• You are the one who connects the prototype to production.
• You will design and build the ML engineering for the pricing engine — the inference serving, training pipelines, and feature engineering — so that complex models run in real time with low latency on Ray.
• Focus on modeling and ML code; the platform and runtime are owned by the MLOps/Platform team, with whom you will work closely.
• Inference serving — design the pipeline of chained models on Ray Serve — model composition, low latency, and update strategies.
• Distributed training — build training pipelines (Ray Train/Data), HPO (Ray Tune), and per-tenant trained models with resilient checkpointing.
• Feature engineering — define and materialize features in the feature store (Feast/Redis), ensuring consistency between training and production.
• Optimization and RL — implement and optimize the optimization components (linear programming) and offline RL of the pricing pipeline.
• Model quality — monitor drift from a modeling perspective, validate versions, and produce explainability (SHAP) — in partnership with MLOps.
• Technical leadership — serve as a reference, mentor, and define with the team what is feasible and scalable.
• You perform handoffs with data scientists, receive data from data engineers, and deliver to the MLOps/Platform team for deployment and operation.

Senior Machine Learning Engineer

• You will architect and evolve the datalake that is the company's data nervous system — the foundation that feeds, in real time, the dynamic pricing engine, ML models, and the group's business intelligence.
• This is an ownership role: you define the multi-tenant Lakehouse architecture, from streaming to the semantic layer, and are responsible for its reliability, governance, and cost.
• Design and evolve the data lake on Apache Iceberg over S3 — well-defined layers, partitioning and compaction, time-travel and support for DELETE/UPDATE for LGPD (Brazilian data protection law).
• Build real-time ingestion (Kafka, Flink, CDC with Debezium) with controlled schema evolution (Schema Registry) and delivery guarantees.
• Model the transformation layer in dbt and orchestrate batch and quality flows in Airflow, from crawler to backfill.
• Maintain metric definitions in Cube.js — the single source that feeds BI and AI agents and ensures consistency across the company.
• Operate federated and low-latency OLAP queries over the lake, with cost and access isolation by tenant and performant queries.
• Ensure data testing, lineage and cost efficiency, keeping the platform reliable as it scales.

Senior Data Engineer

• Atuar no ciclo completo de desenvolvimento, desde a concepção até a entrega, focado na melhoria da confiabilidade e performance dos sistemas.
• Desenvolver e manter aplicações backend e frontend, garantindo a integração eficiente e a alta disponibilidade dos serviços.
• Aplicar uma boa capacidade analítica para a resolução de problemas complexos, análise lógica e depuração de logs.
• Contribuir ativamente para a definição de padrões de codificação, arquitetura e processos de desenvolvimento da equipe.

Senior Java Full Stack Developer

• Garantir a disponibilidade e a performance dos sistemas críticos de atendimento.
• Liderar tecnicamente a equipe de desenvolvimento, promovendo um ambiente de alta performance e aprendizado contínuo.
• Balancear a inovação com a sustentabilidade técnica dos sistemas.
• Manter-se atualizado com as últimas tendências e tecnologias do mercado, aplicando-as de forma estratégica.
• Promover a cultura de qualidade e as melhores práticas de engenharia de software dentro da squad.

Desenvolvedor Java Full Stack – Especialista

• You will transform demand, occupancy, and purchasing behavior data into models that price a network with thousands of origin-destination pairs and multi-leg routes.
• Conduct exploratory and statistical analysis to discover patterns, generate hypotheses, and guide modeling.
• Model demand and no-shows per origin-destination pair using gradient boosting and time series methods, correcting for censored demand bias (unconstrained demand).
• Estimate price elasticity and willingness-to-pay by segment and route as the basis for price optimization.
• Model seat protection and capacity allocation (fare buckets) on multi-leg routes, balancing load factor and revenue.
• Design A/B tests and causal inference analyses that validate price changes and measure real uplift, with clear statistical rollout criteria.
• Ensure interpretability (e.g., SHAP) to defend each price to the business and regulators.
• Design strategies for routes with limited historical data, starting from literature priors and evolving to ML solutions, on a per-tenant basis.