Senior Data Engineer – Aws (Hybrid Or Remote)

iTRTech Group; São Paulo; Ibrido; BRL 150.000 - 210.000; Tempo pieno

Vantaggi offerti da questo lavoro

Hybrid work model

Remote work options

Descrizione del lavoro

iTRTech Group is seeking a Senior Data Engineer – AWS for hybrid or remote work in Brazil. The role focuses on designing and maintaining scalable cloud data platforms, using PySpark, Redshift, Iceberg, and Airflow.

Candidates from any region in Brazil are welcome, with hybrid options for state capitals and remote options for countryside locations. The ideal candidate has 6+ years of experience, advanced English, and hands-on AWS data engineering skills to support Data Lake, Data Warehouse, and

Competenze

• Advanced English proficiency for communication in international environments.
• Strong hands-on experience with PySpark and distributed data processing.
• Experience with AWS data services and modern data architectures.

Mansioni

• Design, develop, and maintain scalable data ingestion, transformation, and delivery pipelines (ETL/ELT).
• Build and optimize data solutions using PySpark, Redshift, Iceberg, and Airflow.
• Develop and maintain Data Lake, Data Warehouse, and Lakehouse platforms in AWS.

Conoscenze

Distributed data processing

AWS cloud

SQL proficiency

Strumenti

PySpark

Amazon Redshift

Apache Iceberg

Apache Airflow

Descrizione del lavoro

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

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

1. How many years of professional experience do you have in Data Engineering and AWS cloud platforms?
2. What is your hands-on experience with PySpark, Amazon Redshift, Apache Iceberg, and Apache Airflow?
3. Have you designed and implemented Data Lake, Data Warehouse, or Lakehouse architectures in AWS?
4. Can you describe your experience optimizing ETL/ELT pipelines, SQL workloads, and data quality processes?
5. 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