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Salary
$34k – $86k per year (Estimated)
Location
Remote (Brazil)
Seniority
Middle
Employment
Full-Time
Overview
Company
Impact
Profile match
Jobgether is an AI-powered job platform focused on remote and flexible work. It matches candidates with relevant roles using skills and preference-based algorithms, and also offers career coaching and job-search guidance.

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Intermediate Data Engineer based in Brazil.

This is an opportunity to contribute to modern data engineering initiatives within a global, technology-driven environment.

You’ll build and maintain reliable data pipelines that ingest, transform, and process large volumes of information.

The role combines hands-on engineering with opportunities to improve scalability, performance, and automation.

You’ll work across multiple data sources and cloud environments while applying strong engineering and data management practices.

Your work will help teams access trusted, well-structured data for analysis, decision-making, and digital transformation.

You’ll collaborate closely with technical and business stakeholders in a fast-paced, international setting.

This role is well suited to a data engineer looking to deepen their expertise in cloud, distributed processing, and modern data platforms.

Accountabilities

    • Implement ETL/ELT solutions and integrate data across multiple systems and sources, ensuring reliable and efficient data movement.
    • Design, develop, and maintain scalable data pipelines for ingesting, storing, transforming, and processing large volumes of data.
    • Apply data transformation, cleaning, aggregation, and modeling techniques to produce efficient and usable data structures.
    • Develop and maintain data exchange APIs between applications and data platforms.
    • Build and manage pipeline workflows using orchestration tools such as Apache Airflow, Luigi, Mage, or Databricks Workflows, integrating PySpark and/or Scala where appropriate.
    • Optimize PySpark jobs and SQL queries by considering data volumes, query complexity, resource utilization, and overall system performance.
    • Apply software engineering principles, including version control, automated testing, documentation, modular design, and maintainability.
    • Work with AWS, Azure, Google Cloud, and related services to develop and operate cloud-based data solutions.
    • Use automation and infrastructure tools such as Terraform, Azure DevOps, and GitHub Actions to improve development and deployment workflows.
    • Collaborate with engineering and business teams to support data security, compliance, quality, and governance requirements.
    • Contribute to continuous improvement initiatives that enhance the scalability, reliability, and efficiency of data processing systems.
    • Communicate technical findings and solutions clearly while coordinating effectively with other teams and stakeholders.
    • Requirements

      • Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, Systems Analysis and Development, or a related technical discipline.
      • Relevant experience in data engineering, with an intermediate level of proficiency in designing and implementing data pipelines and data integration solutions.
      • Strong programming skills in Python, PySpark, Scala, and SQL, with the ability to manipulate, transform, and process data effectively.
      • Practical understanding of ETL/ELT concepts, data pipeline architectures, data transformation, data modeling, and distributed data processing.
      • Experience with orchestration frameworks such as Apache Airflow, Luigi, Mage, or Databricks Workflows.
      • Experience with cloud platforms such as AWS, Azure, or Google Cloud and their associated data and infrastructure services.
      • Familiarity with Infrastructure as Code and automation tools such as Terraform, Azure DevOps, and GitHub Actions.
      • Understanding of software design principles and best practices for building maintainable and scalable data engineering solutions.
      • Experience optimizing SQL queries and PySpark workloads for performance and scalability.
      • Familiarity with data ingestion, transformation, analysis, and visualization tools.
      • Understanding of API development and data exchange between applications.
      • Strong logical reasoning, analytical thinking, and problem-solving abilities.
      • Ability to work autonomously, prioritize tasks, meet deadlines, and consistently deliver high-quality work.
      • Strong communication and interpersonal skills, with the ability to explain technical topics and collaborate effectively with cross-functional teams.
      • Intermediate English proficiency.
      • Benefits

        • Performance-based bonus*
        • Attendance bonus*
        • Private pension plan
        • Meal allowance
        • Health, dental, and life insurance plans
        • Transportation allowance
        • Childcare assistance
        • Days off*
        • Discounts on medications
        • Discounts on company products*
        • Partnership with WellHub
        • Clube Ben partnership
        • Scholarship program*
        • School supplies support
        • Language learning platforms and professional training
        • Casual office environment and dress code
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