Data Engineer

Calyptus; Jaboatão dos Guararapes; Presencial; BRL 80.000 - 120.000; Tempo integral

Resumo da oferta

A data solutions company is seeking a Data Engineer in Brazil to design and build data pipelines that integrate various enterprise data sources for AI processing. The ideal candidate will have over 3 years of experience in data engineering, strong skills in Python and SQL, and familiarity with cloud platforms such as AWS and Azure. Responsibilities include developing data connectors and ensuring data quality for AI models. This role offers significant opportunities for collaboration with data scientists and engineers.

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.

Responsabilidades

• Design and build data pipelines integrating diverse data sources for AI processing.
• Develop connectors and adapters for enterprise systems.
• Implement data quality frameworks for AI model inputs.

Conhecimentos

Data engineering

Python

SQL

ETL / ELT tools

Cloud platforms

Data privacy

Data governance

Formação académica

Bachelor's degree in Computer 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