Data Engineer (Aws, Redshift & Spark) (Hybrid Or Remote)

iTRTech Group; São Paulo; Hybrid; BRL 180,000 - 260,000; Full time

Job summary

EY BR in Brazil is seeking a Senior Data Engineer to design scalable cloud data solutions using AWS Glue, Apache Spark, and Amazon Redshift. You will build reliable data pipelines and models to support analytics for international clients.

The role requires 6+ years of experience, advanced English, and a degree in a related field. Hybrid or remote work options apply, with a focus on data quality and collaboration across global teams.

Qualifications

• Bachelor's degree in Information Systems, Computer Science, Data Engineering or related field.
• Advanced/Fluent English (C2) for communication with international clients.
• Proven hands-on experience developing AWS-based data solutions with Glue, Spark and Redshift.
• Strong programming skills in Python or Scala for data processing and transformation.
• Solid understanding of Data Warehousing concepts, architectures and best practices.
• Strong experience with SQL and Database Management Systems (DBMS).
• Experience developing, maintaining and optimizing ETL pipelines.
• Ability to troubleshoot data processing issues and ensure data quality and integrity.

Responsibilities

• Design, develop, and implement scalable data solutions using AWS Glue, Apache Spark, and Amazon Redshift.
• Build and manage ETL pipelines to extract, transform, and load data from multiple sources.
• Optimize Apache Spark workflows to improve data processing efficiency and performance.
• Develop and maintain data models and schemas in Amazon Redshift to support analytics and reporting.
• Collaborate with Data Engineers and Data Scientists to translate business requirements into technical data solutions.
• Monitor, troubleshoot, and optimize data pipelines, ensuring data quality, reliability, and integrity.
• Maintain technical documentation covering data processes, architecture, and best practices.

Skills

Python

Scala

SQL

AWS Glue

Apache Spark

Amazon Redshift

Data Warehousing

ETL

Data Pipelines

Education

Bachelor's degree in Information Systems, Computer Science, Data Engineering

Job description

DATA ENGINEER (AWS, REDSHIFT & SPARK) (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/Fluent English (C2) for communication with international clients

Seniority: Senior (6+ years)

Rate: Candidates should provide their salary expectations

About the Opportunity

We are looking for an experienced Data Engineer to design, develop, and optimize scalable cloud-based data solutions using AWS Glue, Apache Spark, and Amazon Redshift.

The professional will collaborate with Data Engineers, Data Scientists, and international stakeholders to build reliable data pipelines, optimize data processing, and support analytics and reporting initiatives.

Responsibilities

• Design, develop, and implement scalable data solutions using AWS Glue, Apache Spark, and Amazon Redshift.
• Build and manage ETL pipelines to extract, transform, and load data from multiple sources.
• Optimize Apache Spark workflows to improve data processing efficiency and performance.
• Develop and maintain data models and schemas in Amazon Redshift to support analytics and reporting.
• Collaborate with Data Engineers and Data Scientists to translate business requirements into technical data solutions.
• Monitor, troubleshoot, and optimize data pipelines, ensuring data quality, reliability, and integrity.
• Maintain technical documentation covering data processes, architecture, and best practices.

Requirements

• Bachelor's degree in Information Systems, Computer Science, Data Engineering, or a related field.
• Advanced/Fluent English proficiency (C2) for communication with international clients.
• Proven hands-on experience developing AWS-based data solutions, particularly with AWS Glue, Apache Spark, and Amazon Redshift.
• Strong programming skills in Python or Scala for data processing and transformation.
• Solid understanding of Data Warehousing concepts, architectures, and best practices.
• Strong experience with SQL and Database Management Systems (DBMS).
• Experience developing, maintaining, and optimizing ETL pipelines.
• Ability to troubleshoot data processing issues and ensure data quality and integrity.

Ideal Candidate Profile

A Senior Data Engineer with strong hands-on expertise in AWS cloud data platforms, particularly AWS Glue, Apache Spark, and Amazon Redshift. The ideal candidate demonstrates proficiency in Python or Scala, SQL, and Data Warehousing, with the ability to design scalable data pipelines, optimize processing performance, and collaborate effectively with international teams.

5 Questions for Candidates

1. How many years of professional experience do you have in Data Engineering and AWS cloud environments?
2. What is your hands-on experience with AWS Glue, Apache Spark, and Amazon Redshift?
3. Have you developed and optimized ETL pipelines using Python or Scala?
4. Can you describe your experience with SQL, Data Warehousing, Redshift data modeling, and performance optimization?
5. What are your current salary, salary expectations, and availability to work in a hybrid or remote model in Brazil?

Keywords

Data Engineer, Senior Data Engineer, AWS, Amazon Web Services, AWS Glue, Apache Spark, PySpark, Amazon Redshift, Python, Scala, SQL, Data Engineering, Data Warehousing, ETL, Data Pipelines, Data Modeling, Cloud Data Platform, Data Processing, Data Transformation, Data Quality, Data Integrity, Database Management Systems, DBMS, Performance Optimization, Cloud Computing, Data Analytics

#EY BR