Data Engineer

Calyptus; Osasco; Presencial; BRL 100.000 - 130.000; Tempo integral

Resumo da oferta

A leading technology firm in Brazil is seeking a skilled Data Engineer to design and build data pipelines, integrating diverse enterprise data sources for AI processing. The ideal candidate will have over 3 years' experience in data engineering, strong proficiency in Python and SQL, and familiarity with cloud platforms like AWS or Azure. This role involves developing connectors for enterprise systems and ensuring data quality and compliance. A Bachelor's degree in a relevant field is required.

Qualificações

• 3+ years experience with data engineering in enterprise environments.
• Strong proficiency in Python and SQL for data processing and transformation.
• Experience with cloud platforms and data architecture.

Responsabilidades

• Design and build data pipelines that integrate diverse enterprise data sources.
• Develop connectors and adapters for enterprise systems.
• Implement data quality frameworks and validation systems.

Conhecimentos

Data engineering

Python

SQL

ETL tools

Data integration patterns

Cloud platforms (AWS, Azure, GCP)

Containerization

Formação académica

Bachelor's degree in Computer Science, Engineering, Data Science, or related field

Descrição da oferta de emprego

Overview

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Qualifications

• 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

Responsibilities

• 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