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 Senior Data Developer 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 Responsibilities:
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Design, develop, and maintain scalable data pipelines and infrastructure.
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Collaborate with cross-functional teams to ensure data integrity and usability.
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Document data workflows, processes, and architectures.
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Integrate data quality into data pipelines.
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Develop CI/CD pipelines for ETL processes.
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Implement dimensional data modeling.
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Implement Data Lake/Data Warehouse solutions.
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Implement Data Governance practices (catalog, lineage, etc).
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Provide technical support and troubleshooting for data-related issues.
Must have:
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Solid experience in data engineering or a related role.
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Advanced English (reading, writing, and speaking).
- Experience with the Databricks platform is a must-have for this position.
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Strong knowledge of Spark, Python, and SQL.
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Knowledge of CI/CD pipelines for ETL processes.
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Expertise in dimensional data modeling.
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Experience with Data Lake/Data Warehouse implementations.
- Experience with Azure Devops and Azure Data Factory.
Nice to have:
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Databricks certification is a plus.
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Experience working with international clients.
- Experience with Power BI.
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Familiarity with Data Quality practices.
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Familiarity with Data Governance using Unity Catalog.
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Knowledge of FinOps as applied to the data space.
- Experience with SAP.
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