Engenheiro de Dados e Automação PL

New
Remote in BrazilFull-TimeMiddle
Salary not disclosed
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Job Details

Experience
3+ years
Required Skills
PythonSQLMicrosoft AzureC#.NETCI/CDGenerative AI

Requirements

  • 3+ years of experience in Data Engineering, Automation, or Software Engineering roles.
  • Strong proficiency in Python and/or .NET (C#).
  • Solid experience in API development and system integration (REST, Webhooks, OAuth, JSON).
  • Strong knowledge of SQL and data manipulation techniques.
  • Experience with workflow automation and orchestration tools.
  • Familiarity with cloud environments, preferably Microsoft Azure.
  • Understanding of CI/CD pipelines, Git, and modern development practices.
  • Knowledge of AI concepts such as RAG, prompt engineering, and knowledge base integration.
  • Awareness of FinOps principles and cloud cost optimization is a plus.
  • Strong analytical mindset, collaborative attitude, and innovative thinking.
  • Experience applying generative AI in real-world business scenarios is highly desirable.
  • Familiarity with certifications such as AZ-900, AI-102, DP-900, PL-900, or equivalent is a plus.

Responsibilities

  • Develop and evolve intelligent automation solutions using AI, LLMs, and modern orchestration tools.
  • Design and implement APIs, microservices, and system integrations between internal and external platforms.
  • Build and maintain data pipelines, event-driven workflows, webhooks, and messaging-based architectures.
  • Work with automation platforms such as N8N, Power Automate, and custom workflow engines.
  • Integrate AI capabilities into solutions, including generative AI, semantic search, and knowledge-based systems.
  • Develop data-driven solutions for dashboards, BI, and actionable business insights.
  • Monitor, optimize, and ensure performance, scalability, and reliability of automation services.
  • Apply engineering best practices including version control, CI/CD, testing, and observability.
  • Document solutions and collaborate with cross-functional teams including data, product, and business stakeholders.
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