[Job-31424] Mid-level Data Engineer, Brazil

Team: Prod_Pyxis

Location: Brazil

Commitment: Homeoffice

Workplace Type: remote

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.

At CI&T, we're growing fast and looking for a talented, motivated
Mid Level 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

• 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.

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

Qualifications

• Good communication skills (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.

• Previous experience with 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 or 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.