Data Engineer

Calyptus; Olinda; Presencial; BRL 120.000 - 150.000; Tempo integral

Resumo da oferta

A leading technology firm in Brazil seeks an experienced Data Engineer to design and build data pipelines for AI processing. This role involves developing connectors for enterprise systems, implementing data quality frameworks, and collaborating with global teams. Candidates should possess 3+ years of data engineering experience, strong Python and SQL skills, and familiarity with cloud platforms. Join a dynamic team focused on optimizing data workflows for performance and compliance.

Qualificações

• 3+ years experience with data engineering in enterprise environments.
• Strong proficiency in Python and SQL for data processing and transformation.
• Knowledge of enterprise data standards and APIs (REST, GraphQL, SOAP).

Responsabilidades

• Design and build data pipelines that integrate enterprise data sources for AI processing.
• Develop connectors for enterprise systems (CRM, ERP, databases).
• Implement data quality frameworks for AI model inputs.

Conhecimentos

Data engineering experience

Python proficiency

SQL proficiency

ETL / ELT tools experience

API knowledge

Cloud platforms experience

Containerization familiarity

Formação académica

Bachelor's degree in Computer Science, Engineering, Data Science

Ferramentas

AWS

Azure

GCP

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