CI&T

Software Engineer

• We are looking for adaptable, hands-on Data Integration Developers to help our client migrate multiple domains of business data to their new strategic data platform.
• This will primarily involve migrating data from the current data platform to a newly built Snowflake solution.
• It will also involve supporting development teams as they evolve the data and event models of business applications to integrate with the new technology.
• Participate in defining and implementing scalable and robust data architectures that can be used to deliver AI-enabled business solutions.
• Support downstream initiatives to develop generative AI use cases against the migrated data, and contribute to the iterative evolution of strategic data products and services.

Senior Data Integration Developer

Data Engineer

• Ensure the integrity, consistency and efficiency of data models across the ecosystem by conducting structural reviews, defining standards and enforcing governance.
• Analyze and redesign conceptual, logical and physical models for simplification and efficiency (On-premises and Cloud).
• Identify redundancies, obsolete tables and inconsistencies in large databases (e.g., consolidate 500 tables into 100 official ones).
• Apply normalization and denormalization techniques to reduce redundancy without compromising performance.
• Define criteria to establish a single source of truth (Single Source of Truth).
• Ensure data governance: standardization, naming conventions and referential integrity.
• Evaluate indexes, keys and relationships to optimize queries and reduce costs.
• Document models, data dictionaries, diagrams and usage policies.
• Plan migration strategies to leaner, consolidated models.
• Manage access and enforce compliance rules (LGPD, SOX) and encryption.
• Integrate models with MDM solutions to ensure consistency between master systems and transactional databases.
• Define data lifecycle policies: archiving, purging and versioning.
• Collaborate with business areas to validate rules and prioritize critical tables.

Senior Data Engineer – Data Modeling and Governance

Product Manager

• Backlog Management: Define, prioritize, and maintain the product backlog aligned with the company’s vision and strategic objectives.
• Documentation: Conduct functional refinement, document requirements, and write user stories.
• Cross-functional Collaboration: Work closely with development, design teams, and stakeholders to ensure deliveries meet customer expectations.
• Performance Monitoring: Analyze product performance metrics and user feedback to adjust strategy and priorities.
• Effective Communication: Serve as the primary point of contact between stakeholders and the development team, clearly communicating the product vision and expectations.
• Run Scrum meetings and ensure adherence to agile practices.
• Stay up to date on market trends and technological innovations that may impact the product.

Backend Engineer

• - Atuar com o time de desenvolvimento em uma entrega de qualidade para nosso cliente;
• - Atuar com resolução de problemas de forma mais assertiva;
• - Participar do dia a dia do time contribuindo para passagem de conhecimento;
• - Atualizar os status das atividades nas ferramentas de controle;
• - Fazer uso e dominar AI em seu dia a dia.

Senior Java Developer

• Define and prioritize the product roadmap for data initiatives, ensuring alignment with business goals.
• Collaborate with data engineers and architects to translate business requirements into technical specifications.
• Oversee the entire product lifecycle from ideation to launch and beyond.
• Conduct market research and gather user feedback to inform product enhancements.
• Ensure that data products adhere to quality standards and meet user needs.

Data Product Manager

• Design and implement large-scale data ingestion and processing architectures;
• Develop robust solutions using Azure Data Fabric, Databricks and related services;
• Work with NoSQL databases, including MongoDB and Cosmos DB;
• Ensure data quality, governance and security across all stages of the data lifecycle;
• Collaborate with multidisciplinary teams to integrate data from different sources;
• Propose continuous improvements to existing processes and architectures;
• Document solutions and best practices to ensure system maintenance and evolution.

Senior Data Engineer

Artificial Intelligence

• Lead and develop the team, promoting engineering best practices and a Data-as-a-Product culture (domain ownership, SLOs/SLIs).
• Design and implement complex data pipelines (batch and streaming), with automation, orchestration, and ETL/ELT optimization.
• Develop transformations in Python/PySpark and SQL, with automated tests (PyTest) and engineering standards.
• Ensure end-to-end Data Quality: tests-as-code, dataset SLOs/SLIs, proactive alerting, and remediation automation.
• Design the platform blueprint: metadata-first, lineage, policy-as-code, data catalog/discovery, semantic layer, and observability.
• Incorporate GenAI into workflows: copilots for catalog and documentation, sensitive data classification (PII), assisted generation of policies and tests, and change intelligence (impact summaries).
• Collaborate with multidisciplinary teams (data, product, security, compliance, business), translating business requirements into scalable, measurable technical solutions.
• Drive architectural decisions (Lakehouse, Delta/Parquet, real-time with Pub/Sub/Kafka, microservices) with a focus on scalability, cost, and security.
• Operate always-on compliance mechanisms (LGPD/PII): classification, masking, contextual access control, and end-to-end traceability.
• Integrate the platform with the corporate ecosystem (APIs, events, legacy systems/SaaS), ensuring performance and reliability.
• Deploy versioning, CI/CD, and IaC (Git/Azure DevOps) for reproducibility and reduced time-to-data.
• Interact with senior management, present roadmaps, risks and results; define and track OKRs/metrics (adoption, lead time, incidents, residual risk).
• Evangelize and manage change to increase adoption and business value.

Data & AI Manager – Master

Risk

• Establishing milestones for Data Domains in their Data Ownership journey.
• Builds long-term, strategic relationships with Data Owners and Data Stewards.
• Drives acceptance of Data Governance and facilitates the engagement of stakeholders in support of the delivery of Business Glossary, Metadata Management, Access Policies and Terms of use.
• Identifies the impact of internal or external events, regulations and business use cases on ASOS’s use of data and creates processes to manage compliance.
• Leads and plans activities to implement data management strategies with Technical teams.
• Builds strong alliance with Data Architecture and Data Engineering.
• Implementing and driving adoption of Data Governance Tools such as Data Catalogues and Data Observability, championing business user requirements in the development of these tools.
• Advocate Data Quality initiatives and experience implementing Data Quality Frameworks.
• Engage with Data Stewards to resolve complex data quality issues as they relate to specific Data Domain requirements.
• Supporting team members, offering training and mentorship.
• Creating and supporting collaborative ways of working across the Data Governance Teams.

Data Governance Analyst – FTC

• Support a data modernization initiative migrating core systems from Amazon Redshift to Snowflake
• Build and maintain data ingestion pipelines from APIs and SFTP sources
• Implement ELT transformations using SQL and dbt (or similar)
• Support incremental loads, historical backfills, and schema changes
• Monitor and troubleshoot pipeline failures
• Create and maintain Snowflake tables, views, and tasks
• Optimize queries and warehouse usage for performance and cost
• Follow defined modeling, naming, and governance standards
• Work closely with the Data Architect to implement target designs
• Collaborate with the Data Product Manager on data requirements
• Participate in agile ceremonies (standups, planning, reviews)
• Document pipelines and data assumptions clearly

Midlevel Data Engineer

QA Engineer

• Validate that development complies with the approved documentation.
• Perform technical tests on implemented pipelines, scripts, and processes.
• Create and execute test scenarios to ensure data integrity and consistency.
• Manage detailed evidence of: development performed / deployment to environments / tests executed and their results / acceptance testing and system behavior.
• Ensure that the implemented solution behaves correctly and adheres to requirements.
• Document the entire QA process, including checklists, scripts, and results.
• Support the standardization of validation and acceptance processes.

QA Mid Level

• Develop software solutions using Python, following engineering best practices.
• Implement and evolve microservices and REST APIs.
• Work on front-end development using React and Next.js, in collaboration with the team.
• Write clean, testable, and maintainable code, participating in code reviews.
• Contribute to the creation and maintenance of automated tests and CI/CD pipelines.
• Collaborate with the team on analysis of technical and business requirements.
• Support continuous improvement initiatives for development processes and standards.
• Work in cloud environments (preferably Azure), supporting the implementation and operation of solutions.
• Contribute to AI and automation solutions, under the guidance of more experienced professionals.

Mid-Level Python Developer

Android Engineer

• Develop complex features and mechanisms as needed.
• Ensure the quality of the team's deliverables through code reviews, static analyzers, and automated tests.
• Participate in business rituals and contribute to the technical specification of solutions.
• Act as a guardian of Continuous Delivery by promoting technical discussions and raising important points for the squad's evolution.
• Work with a focus on results and improving the team's efficiency through engineering practices.
• Treat the product as if it were your own.

Senior/Mid-level Developer, Android

Frontend Engineer

• Atuar como protagonista de transformação digital, cultural, na maior instituição bancária do Brasil;
• Buscar e prezar pela melhoria contínua de processos e práticas de engenharia;
• Atuar com foco no impacto a ser gerado pela solução e na experiência do usuário;
• Colaborar com equipes multidisciplinares para projetar, desenvolver e implementar soluções eficientes;
• Manter e aprimorar continuamente os sistemas existentes.

Senior Frontend Developer, React

• Development and maintenance of robust solutions using .NET 8 / Angular 18+.
• Working on large-scale, mission-critical applications with a focus on REST APIs, business logic, and database integration.
• Applying modern software engineering and cloud practices (Azure).

Senior Developer – FullStack, .NET/Angular

• Atuar como referência técnica e de arquitetura junto ao cliente, garantindo alinhamento com objetivos de negócio.
• Participar de discussões de design e arquitetura, propondo soluções técnicas robustas e sustentáveis.
• Estruturar backlogs técnicos, apoiar o refinamento de estórias e orientar o time em decisões estratégicas.
• Assegurar que as soluções estejam em conformidade com as melhores práticas de segurança, desempenho e escalabilidade.
• Criar e manter documentações técnicas e de design, conforme as necessidades do cliente.
• Diagnosticar e resolver problemas técnicos complexos, fornecendo direcionamento e alternativas viáveis.
• Atuar de forma colaborativa com times multidisciplinares, alinhando soluções técnicas e de negócio.
• Compreender requisitos e definir frameworks, tecnologias e padrões arquiteturais adequados.
• Contribuir para a implementação e evolução de pipelines CI/CD e provas de conceito.