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[Job-31421] Senior Data Engineer, Brazil
Ciandt · Brazil
Publicada em 01/09/2026
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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.
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