Engenheiro de Dados - Sênior | PySpark e AWS in Brazil, Indiana at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Engenheiro de Dados - Sênior | 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.

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

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

• 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