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Salary
$41k – $105k per year (Estimated)
Location
Remote (Brazil)
Seniority
Senior
Overview
Company
Impact
Profile match
Ciandt is a leading provider of digital transformation services. We help organizations transform their businesses by leveraging the latest technologies. Our solutions provide comprehensive digital strategy, design, development, and implementation capabilities.

** 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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