SENIOR DATA ENGINEER – AWS (HYBRID OR REMOTE)

SENIOR DATA ENGINEER – AWS (HYBRID OR REMOTE BRAZIL)

Company hires for hybrid or remote position

?? Location: Brazil — candidates from any region are welcome

?? Only candidates already based in Brazil will be considered

?? Work Model: Hybrid for candidates living in state capitals and Remote for candidates living in countryside/cities outside the state capitals

??? Language Requirements: Advanced English for professional communication

?? Seniority: Senior (6+ years)

??Rate: Candidates should provide their salary expectations

?? Instructions: Please send your CV in English and make sure to include all skills and experience that match the requirements of the opportunity. This will significantly increase your chances of success.

About the Opportunity

We are looking for an experienced Senior Data Engineer – AWS to design, develop, and maintain scalable cloud-based data platforms in complex enterprise environments.

The professional will work with PySpark, Amazon Redshift, Apache Iceberg, and Apache Airflow, building high-performance data pipelines and supporting modern Data Lake, Data Warehouse, and Lakehouse architectures.

Responsibilities

• Design, develop, and maintain scalable data ingestion, transformation, and delivery pipelines.
• Build and optimize data solutions using PySpark, Amazon Redshift, Apache Iceberg, and Apache Airflow.
• Develop and maintain cloud-based Data Lake, Data Warehouse, and Lakehouse platforms.
• Implement and improve high-performance ETL and ELT frameworks.
• Ensure data quality, reliability, scalability, and performance across pipelines and analytical workloads.
• Monitor production workloads, troubleshoot issues, and optimize data processing.
• Collaborate with architects, analysts, and business stakeholders on technical solutions.
• Support data governance, architecture reviews, code reviews, and cloud platform modernization.

Requirements

• Strong professional experience in Data Engineering and cloud-based data platforms.
• Advanced English proficiency for communication in international environments.
• Strong hands-on experience with PySpark and distributed data processing.
• Practical experience with Amazon Redshift and Apache Iceberg.
• Experience with Apache Airflow for data pipeline orchestration.
• Solid knowledge of AWS services for data engineering and analytics.
• Experience designing scalable ETL/ELT pipelines and Data Lake, Data Warehouse, and Lakehouse architectures.
• Advanced SQL skills, analytical workload optimization, data monitoring, governance, and quality management.

Ideal Candidate Profile

A Senior Data Engineer with strong expertise in AWS cloud data platforms, distributed processing, and modern data architectures. The ideal candidate has hands-on experience with PySpark, Redshift, Iceberg, and Airflow, demonstrating the ability to build reliable, scalable data pipelines and optimize complex enterprise data environments.

5 Questions for Candidates

• How many years of professional experience do you have in Data Engineering and AWS cloud platforms?
• What is your hands-on experience with PySpark, Amazon Redshift, Apache Iceberg, and Apache Airflow?
• Have you designed and implemented Data Lake, Data Warehouse, or Lakehouse architectures in AWS?
• Can you describe your experience optimizing ETL/ELT pipelines, SQL workloads, and data quality processes?
• What are your current salary, salary expectations, and availability to work in a hybrid or remote model in Brazil?

Keywords

Senior Data Engineer, AWS, Amazon Web Services, PySpark, Apache Spark, Amazon Redshift, Apache Iceberg, Apache Airflow, Data Engineering, Data Lake, Data Warehouse, Lakehouse, ETL, ELT, SQL, Data Pipelines, Cloud Data Platform, Data Governance, Data Quality, Distributed Data Processing, Data Architecture

#EY BR