At CI&T, we help large enterprises transform the potential of AI into real business impact with AI Deployment, AI-native execution, and tech-integrated business solutions.

With 30 years of experience in technological transformation, we accelerate innovation with expertise in Agentic SDLC, Application modernization, Data & AI, Martech and Business strategy.

We are 8,000 CI&Ters across more than 25 countries, collaborating to build solutions with real impact. AI is already part of how we work, evolve, and innovate every day.

** Must have good English =>  C1 or above

At CI&T, we're growing fast and looking for a talented, motivated Data Engineer to join our team. You'll play a crucial role in designing, developing, and maintaining scalable data pipelines and infrastructure to drive data analytics and machine learning solutions for our global clients.

Key Responsabilities 

• Design, develop, and maintain scalable data pipelines and infrastructure.

• Collaborate with cross-functional teams to ensure data integrity and usability.

• Document data workflows, processes, and architectures.

• Integrate data quality into data pipelines.

• Develop CI/CD pipelines for ETL processes.

• Implement dimensional data modeling.

• Implement Data Lake/Data Warehouse solutions.

• Implement Data Governance practices (catalog, lineage, etc).

• Provide technical support and troubleshooting for data-related issues.

Qualifications 

• Good English communication skills is mandatory (reading, writing, and speaking).

• Proven experience working with modern data engineering stacks in the cloud.

• Experience with the Databricks platform is a must-have for this position.

• Strong knowledge of Spark, Python, and SQL.

• Knowledge of CI/CD pipelines for ETL processes.

• Expertise in dimensional data modeling.

• Experience with Data Lake/Data Warehouse implementations.

Nice to Have

• Databricks certification is a plus.

• Experience working with international clients.

• Experience working with Azure and AWS.

• Experience with Power BI.

• Familiarity with Data Quality practices.

• Familiarity with Data Governance using Unity Catalog.

• Knowledge of FinOps as applied to the data space.