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Data Engineer
Job summary
A technology company based in Manaus, Brazil, is seeking a data engineer with over 3 years of experience in data engineering within enterprise environments. The ideal candidate will have strong proficiency in Python and SQL, along with experience in ETL/ELT tools and cloud platforms like AWS, Azure, or GCP. This role involves designing data pipelines, establishing data governance, and collaborating with data scientists to meet model requirements. The position offers a dynamic work environment focused on AI processing and data integration.
Responsibilities
- Design and build data pipelines that integrate diverse enterprise data sources for AI processing.
- Develop connectors and adapters for enterprise systems like CRM, ERP, and databases.
- Implement data quality frameworks and validation systems for AI model inputs.
- Create secure data handling workflows that support global development teams.
- Build data transformation pipelines for unstructured and structured data.
- Establish data governance and lineage tracking for compliance and audits.
- Optimize data processing workflows for scale and performance.
- Collaborate with data scientists and AI engineers to ensure data meets model requirements.
Skills
Education
- 3+ years experience with data engineering in enterprise environments
- Strong proficiency in Python and SQL for data processing and transformation
- Experience with ETL / ELT tools and data integration patterns
- Knowledge of enterprise data standards and APIs (REST, GraphQL, SOAP)
- Understanding of data privacy, security, and access control best practices
- Experience with cloud platforms (AWS, Azure, GCP) and data infrastructure
- Familiarity with containerization and orchestration tools
- Bachelor's degree in Computer Science, Engineering, Data Science, or related field
- Design and build data pipelines that integrate diverse enterprise data sources for AI processing
- Develop connectors and adapters for enterprise systems (CRM, ERP, document management, databases)
- Implement data quality frameworks and validation systems for AI model inputs
- Create secure data handling workflows that support global development teams
- Build data transformation pipelines that prepare unstructured and structured data for AI models
- Establish data governance and lineage tracking for compliance and audit requirements
- Optimize data processing workflows for scale and performance
- Collaborate with data scientists and AI engineers to ensure data meets model requirements
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.