Leega

Android Engineer

• Integrate the app with predictive recommendation APIs (personalized storefront) and smart checkout
• Implement flows for logged-in users, including pre-selection of payment method
• Instrument analytics events (GA4) to support the recommendation engine
• Collaborate with data and backend teams to define API contracts
• Participate in agile rituals: daily stand-up, planning, check-point, and sprint review

Mid-level Android Developer

Backend Engineer

• Develop APIs for client services using technologies such as PHP, Laravel, and MySQL.
• Participate in and develop integrations for collection and return files using Python Lambdas.

Mid-level PHP, Python Developer

AI Engineer

• Design, implement, and optimize the data infrastructure that supports AI and machine learning (ML) solutions
• Ensure data availability, quality, and security
• Ingest and transform data for the data lake and Feature Store
• Develop and support the operationalization of AI and ML models
• Conduct complex analyses and monitor data quality

Senior AI Engineer, ADK GCP

• Atender demandas de sistemas críticos
• Trabalhar com processamento de alta volumetria
• Análise e otimização de queries
• Desenvolvimento de soluções integradas

Desenvolvedor Sênior – Oracle PL/SQL, .NET

• Lead the team technically, defining architectural patterns, design, and engineering best practices in Java and Python.
• Drive solution and data architecture decisions on AWS, focusing on scalability, security, cost, and observability.
• Serve as a technical reference in code reviews, design reviews, and day-to-day trade-off decisions.
• Incorporate AI tools (code assistants, automations, agents) into the team's workflow to increase productivity and quality.
• Work side-by-side with Product and other squads in agile ceremonies, helping to break down scope, estimate, and prioritize.
• Mentor and develop team members, contributing to their technical growth and career development.
• Perform exploratory analyses of environments and technologies, documenting findings and training the technical team.
• Work closely with the team and stakeholders to define and refine product requirements.
• Collaborate closely with the DevOps team on deployment, monitoring, and application support activities.
• Promote continuous improvements in code and processes across the organization.
• Ensure production reliability and quality (monitoring, incident response, and technical debt reduction).

Tech Lead – Java & Python Development

Consultant

• Conduct surveys and diagnostics to understand the client's processes, challenges and needs.
• Support the mapping of technical and business requirements to build appropriate solutions.
• Work directly on the implementation of Matera solutions, such as clearing, reconciliation and settlement systems (Matera CCS), payment methods and digital banking.
• Participate in the configuration and implementation of Matera JUD solutions (judicial/legal demands).
• Collaborate with the development team to adapt and customize products according to the requirements of each project.
• Execute and monitor integration and acceptance testing (UAT), ensuring the quality and operation of solutions before production.
• Monitor the performance of implemented solutions and report opportunities for improvement and system optimization.
• Stay up to date with new regulations and market practices to suggest innovations in solutions.
• Work collaboratively with internal and external stakeholders to ensure expectation alignment and smooth project delivery.

Mid-level Matera Solutions Consultant, CCS/JUD

Analytics Engineer

• This is not a role focused solely on processing data or building complex dashboards. We are looking for a professional who will act as the official “translator” of data for the business. You will be the right hand of strategy, turning SQL into persuasive narratives and recommendations that directly move the company needle.
• Your mission will be to “hunt” for opportunities through consumer behavior and market studies, ensuring that data answers business questions in an intelligent, visual, and strategic way.
• Impact Analysis: Conduct deep studies on consumer profiles and market behavior.
• Executive Storytelling: Turn complex data into clear, fluid, and persuasive presentations (emphasis on PowerPoint and oral presentations).
• Influence and Advocacy: Defend recommendations and actively participate in discussion forums and meetings with executive leadership.
• Business Partnership: Work with a product/business mindset closely alongside UX Designers, ensuring analysis focuses on the customer experience.
• Versatile Interface: Connect with multiple areas to understand pain points and propose evidence-based solutions, supporting financial and performance decisions.
• Design and build scalable, resilient data analytics solutions in the GCP environment;
• Define strategies for implementing and building key metrics;
• Propose and implement architectural improvements;
• Gather requirements from business areas and document them;
• Be familiar with agile methodologies;
• Align the corporate IT environment with business needs, standards, and market best practices;
• Be capable of embedding a data-driven culture into day-to-day activities;
• Have the ability to work in a team with empathy, be able to listen and be heard, and possess strong communication skills.
• Be adaptable to dynamic work scenarios;

Senior Analytics Engineer, GCP

Data Engineer

• Lead the design and evolution of data architecture (Data Lake, Data Warehouse, Lakehouse)
• Design, develop and optimize high-scale data pipelines (ETL/ELT)
• Act as the technical reference for the data engineering team
• Work with distributed processing using Databricks (Spark/PySpark)
• Define development, testing and deployment best practices (DataOps)
• Ensure data governance, quality, security and reliability
• Optimize performance and costs in GCP environments
• Integrate multiple data sources (batch and streaming)
• Support BI, Analytics and Data Science teams in delivering data
• Participate in strategic decisions related to data and technology

Senior Data Engineer, GCP

• Solution Lifecycle: Work end-to-end, responsible for specification, development, deployment, support for acceptance testing, and continuous maintenance of solutions.
• Solution Development: Lead the development and architecture of systems using .NET C#, ensuring application integrity, scalability and security.
• Systems Integration: Design and implement integrations with internal solutions and external partners.
• Acceleration via AI: Methodically incorporate generative AI assistants (such as GitHub Copilot, Claude Code, LLM assistants and related tools) to optimize development turnaround, code refactoring and test automation.
• Business Interface: Actively participate in technical committees and business meetings, proactively translating functional requirements into architectural solutions.
• Technical Documentation: Prepare and keep up-to-date manuals, architecture diagrams and standard operating procedures.
• Deadline Management: Commit rigorously to established schedules, mitigating delay risks through strategic use of technology.

 .NET Developer, Generative AI

Data Scientist

• You will be part of our Data Science team, responsible for developing, maintaining and evolving analytical solutions and machine learning models that support multiple business areas.
• We operate in a collaborative environment with a strong engineering culture, a focus on data quality, and continuous improvement.
• In this project, you will play a strategic role in migrating integrations, pipelines and data consumers currently running on AWS to the GCP ecosystem, ensuring operational continuity, reliability and adherence to data engineering and machine learning best practices.
• Perform the migration of connections, pipelines and data consumption processes from AWS to GCP for the company's Data Science projects.
• Adapt queries, integrations and data processing routines to run in the GCP environment, taking into account differences between services and SQL dialects.
• Execute functional tests, consistency validations and data sign-off after migration processes.
• Support the migration of analytical workloads and machine learning pipelines to equivalent services within the GCP ecosystem.
• Work closely with data engineering, architecture and MLOps teams to ensure stability and efficiency of migrated solutions.
• Identify and resolve issues related to performance, compatibility and governance during the cloud transition.
• Document technical processes, data flows and architectural decisions related to the migration.
• Contribute to standardization, automation and quality improvements in pipelines and analytical processes.

Senior Data Scientist – GCP Migration

Account Executive

• Responsible for managing the full sales cycle for the Digital Analytics business unit, from prospecting through to closing.
• Develop and expand a client portfolio, identifying business opportunities in consulting, implementation and evolution of Digital Analytics solutions.
• Diagnose clients' needs and translate requirements into clear, technical, results-oriented value propositions.
• Lead meetings, executive presentations and product/service demonstrations, articulating Leega's offering with clarity.
• Act as a consultative partner to clients, bridging technical and business areas and ensuring a deep understanding of measurement and digital data challenges.
• Prepare commercial proposals.
• Collaborate with Pre-Sales, Operations, Data Engineering and Customer Success teams to build robust proposals and relevant use cases.
• Map market trends and stay up to date on technologies, frameworks and digital measurement best practices.
• Support the business unit's go-to-market strategy definition, actively contributing to the development of the Digital Analytics portfolio.
• Provide customer support pre- and post-sales.

Sales Executive – Digital Analytics

Business Intelligence Developer

• 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)

Analista de BI Sênior

• **Analysis and Planning of Loads/Pipelines:**
• Evaluate the data warehouse architecture and requirements.
• Map data, transformations and processes to GCP services (Cloud Storage, BigQuery, Dataproc).
• Define data migration strategy (full load, incremental, CDC).
• Develop a data architecture plan on GCP.
• **Design and Data 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 data quality mechanisms.
• **Provisioning and Infrastructure Management:**
• Use IaC tools (Terraform) to provision and manage GCP resources (BigQuery datasets/tables, Cloud Storage buckets, Dataproc clusters).
• Configure and optimize Dataproc clusters for different workloads.
• Manage networking, security (IAM) and access on GCP.
• **Performance and Cost Optimization:**
• Optimize queries in BigQuery 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 apply IAM policies to control access to data and resources.
• Ensure compliance with data governance policies.
• **Monitoring and Support:**
• Troubleshoot performance and functional 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 business areas.
• Ensure clear communication between architecture definitions and software components, and support the evolution and quality of the team's developments.
• **Jira / Agile Methodologies:**
• Familiarity with agile methodologies, ceremonies and proficiency with the Jira tool.

Senior Data Engineer – GCP, DBT

People Operations

• Monitoring turnover and absenteeism metrics
• Conducting 1:1 meetings with teams
• Supporting Coordinators and Managers with client-related requests
• Assisting in the analysis and monitoring of team performance indicators
• Supporting the implementation of Individual Development Plans (IDPs)
• Assisting with internal team movements
• Opening and managing job vacancies
• Assisting with candidate interviews
• Managing and controlling employee vacations

People Partner

• Able to run an entire project with minimal to no supervision
• Design and build mathematical/statistical solutions according to business requirements
• Translate requirements into programmable statistical models, assess timelines, and evaluate 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)
• Ability to guide and teach less experienced team members in any part of the process/lifecycle of a machine learning project
• Create and configure intents, entities, and conversational flows using LLMs
• Develop statistical and mathematical models in Python
• Create and maintain ML projects with CI/CD
• Implement business logic and decision rules in models
• Ensure performance, scalability, and resilience of integrations
• Monitor and optimize the performance of created models
• Assist in mentoring less experienced team members