Data Engineer

Calyptus; Alvorada; Presencial; BRL 100.000 - 150.000; Tempo integral

Resumo da oferta

A leading data technology firm in Rio Grande do Sul is seeking a proficient Data Engineer to design and build data pipelines for AI processing. The ideal candidate will have strong skills in Python and SQL, along with extensive experience in data engineering and cloud platforms. This position involves developing data integration solutions, ensuring data quality, and collaborating with AI engineers to meet model requirements. It offers an exciting opportunity for professional growth in a dynamic environment.

Qualificações

• 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.

Responsabilidades

• 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).
• Implement data quality frameworks and validation systems for AI model inputs.

Conhecimentos

Data engineering

Python

SQL

ETL / ELT tools

Cloud platforms (AWS, Azure, GCP)

Data security

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