Engenheiro de Dados - Sênior | PySpark e AWS

Jobgether · Brazil

Company

Jobgether

Location

Brazil

Type

Full Time

Job Description

Team: IT

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Engenheiro de Dados - SĂȘnior | PySpark e AWS in Brazil.

This role sits at the heart of large-scale data transformation initiatives, where you will design, build, and optimize modern data pipelines that power analytics, AI, and business decision-making. You will work in a highly collaborative, global environment, contributing to the evolution of scalable data platforms on AWS. The position involves handling high-volume data processing, ensuring performance, reliability, and governance across complex data ecosystems. You will play a key role in shaping data architecture decisions and enabling advanced analytics capabilities for enterprise-level clients. Working alongside multidisciplinary teams, you will help translate business needs into robust, production-ready data solutions. This is an opportunity to influence data strategy while working with cutting-edge cloud and big data technologies.

Accountabilities

You will be responsible for building and maintaining scalable data engineering solutions, ensuring high performance, reliability, and alignment with business and analytical needs.

  • Design, develop, and maintain scalable data pipelines using Python and PySpark
  • Build and optimize data processing architectures on AWS (S3, Glue, EMR, Lambda, Redshift)
  • Develop robust ETL/ELT workflows for ingestion, transformation, and processing of large datasets
  • Apply advanced SQL techniques for data manipulation, modeling, and query optimization
  • Design and implement data models for analytical environments such as Data Lakes and Data Warehouses
  • Collaborate on cloud-based data architecture and best engineering practices
  • Use Git for version control and ensure software engineering best practices in data development
  • Contribute to workflow orchestration using tools such as Airflow or similar platforms
  • Support data governance, performance tuning, and system scalability initiatives
  • Work closely with cross-functional teams to translate business requirements into technical solutions

  • Requirements

    You are an experienced data engineer with strong expertise in cloud platforms, distributed processing, and scalable data architecture.

    • Proven experience as a Data Engineer working with large-scale data environments
    • Strong hands-on experience with Python and PySpark for data pipeline development
    • Solid experience with AWS data services (S3, Glue, EMR, Lambda, Redshift)
    • Strong knowledge of ETL/ELT processes and distributed data processing
    • Advanced SQL skills for querying, modeling, and optimization
    • Experience designing Data Lakes and Data Warehouses
    • Familiarity with Git and modern software engineering practices
    • Knowledge of workflow orchestration tools (e.g., Airflow) is desirable
    • Understanding of data architecture, performance optimization, and scalability principles
    • Strong analytical thinking and problem-solving abilities
    • Ability to work in collaborative, global, and fast-paced environments
    • English at advanced or fluent level is a strong plus

    • Benefits

      • Medical assistance fully covered for employee and dependents
      • Dental assistance
      • Meal or food allowance with no salary deduction
      • Life insurance
      • Private pension plan
      • Gympass access for wellness and fitness
      • Employee stock purchase plan with discount
      • Pharmacy discounts (as per policy)
      • Childcare assistance (as per policy)
      • Language school partnerships (as per policy)
      • Extended maternity and paternity leave
      • Performance-based bonus program (PPR, as per policy)
      • Career development within a global organization
      • Exposure to large-scale, international data projects
Apply Now

Date Posted

05/11/2026

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