SENIOR DATA ENGINEER | AWS & DATA PLATFORMS (HYBRID / REMOTE)

iTRTech Group; São Paulo; Híbrido; BRL 260 000 - 380 000; Tempo integral

Resumo da oferta

iTRTech Group in Brazil is seeking a Senior Data Engineer to design, build, and evolve scalable data solutions on AWS. The role combines hybrid or remote work options for candidates based in Brazil, with English at C2 level for international collaboration.

You will work with SQL, Python, and Spark to transform diverse data sources into reliable data products, support data lakes and warehouses, and participate in cloud migration and DataOps practices.

Qualificações

• Bachelor's degree in Computer Science or related field.
• English proficiency at C2 level for international communication.
• Experience designing, developing, and supporting scalable data pipelines.
• Advanced SQL and Python skills.
• Experience with ETL/ELT, data ingestion, integration, and transformation.
• Experience with AWS data services including S3, Glue, Redshift, Athena, Lambda.
• Knowledge of data modeling, Data Warehouse architectures, and Data Lakes.
• Experience with Spark or PySpark.

Responsabilidades

• Design, develop, maintain, and optimize scalable data pipelines.
• Build data ingestion, integration, and transformation processes using SQL, Python, and distributed processing.
• Develop and support AWS solutions using S3, Glue, Redshift, Athena, and Lambda.
• Contribute to Data Lakes, Data Warehouses, and modern data platforms.
• Implement ETL/ELT processes aligned with business needs.
• Process large data volumes using Spark or PySpark.
• Monitor and optimize pipelines, queries, and cloud workloads.
• Embed data quality, security, and governance into engineering.

Conhecimentos

SQL

Python

Apache Spark

Data modeling

AWS data services

Data pipelines

English (C2)

Formação académica

Bachelor's degree in CS/SE or related

Ferramentas

Amazon S3

AWS Glue

Amazon Redshift

Amazon Athena

AWS Lambda

Descrição da oferta de emprego

SENIOR DATA ENGINEER | AWS & DATA PLATFORMS (HYBRID / REMOTE BRAZIL)

Brazilian company hires for hybrid or remote position.

Location: Brazil (any location)

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: English proficiency at C2 level for communication in an international environment.

Seniority: Senior (6+ years).

Compensation: Please inform your salary expectations when applying.

Build reliable data pipelines that power business decisions.

We are looking for an experienced Data Engineer to design, build, and evolve scalable data solutions on AWS.

You will work with SQL, Python, and distributed processing technologies to turn complex data sources into reliable, accessible data. Working alongside architects, engineers, analysts, and global stakeholders, you will contribute to modern data platforms, cloud migration, and continuous improvements in performance and quality.

What you will do

• Design, develop, maintain, and optimize scalable, reliable data pipelines.
• Build data ingestion, integration, and transformation processes using SQL, Python, and distributed processing technologies.
• Develop and support AWS solutions using Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, and AWS Lambda.
• Contribute to the development and evolution of Data Lakes, Data Warehouses, and modern data platforms.
• Implement ETL and ELT processes aligned with technical requirements and business needs.
• Process large data volumes using Apache Spark or PySpark.
• Contribute to architecture discussions, helping shape secure, scalable, and maintainable solutions.
• Monitor and optimize pipelines, queries, transformations, and cloud workloads.
• Troubleshoot data ingestion, processing, storage, and delivery issues, conducting root cause analysis and implementing lasting fixes.
• Embed data quality, integrity, security, and governance into engineering processes.
• Collaborate with architects, software engineers, analysts, and business stakeholders throughout delivery.
• Support cloud migrations and data platform modernization initiatives.
• Implement automation, version control, CI/CD, and DataOps practices.
• Maintain technical documentation, data flows, and operational procedures while ensuring alignment with technical standards, internal controls, and applicable regulatory requirements.
• Share knowledge and contribute to standardization and continuous improvement.

What you bring

• A bachelor's degree in Computer Science, Software Engineering, or a related field.
• English proficiency at C2 level, with the ability to communicate effectively in an international environment.
• Experience designing, developing, and supporting scalable data pipelines.
• Advanced SQL and Python skills.
• Experience with ETL, ELT, data ingestion, integration, and transformation.
• Experience with AWS data services, including Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, and AWS Lambda.
• Knowledge of data modeling, Data Warehouse architectures, and Data Lakes.
• Experience with distributed processing using Apache Spark or PySpark.
• The ability to develop, monitor, optimize, and troubleshoot data pipelines.
• Knowledge of data quality, security, and governance practices.
• Experience working in Agile environments with multidisciplinary and distributed teams.
• Strong analytical skills, autonomy, clear communication, and a commitment to delivery quality.

Experience that will help you stand out

• Databricks or Snowflake.
• Apache Airflow or equivalent orchestration tools.
• dbt.
• Kafka or other messaging and streaming technologies.
• Terraform and Infrastructure as Code.
• Git, automation, and CI/CD pipelines.
• DataOps practices.
• Data platform migration, modernization, or transformation projects.
• Financial institutions, Banking, Wealth Management, Asset Management, or other regulated environments.
• Certifications in AWS, Azure, Databricks, Snowflake, or Data Engineering.

Who would thrive in this role?

You are a hands-on data engineer who enjoys building dependable solutions and understanding how they behave in production. You can move from designing a pipeline to investigating a performance bottleneck, tracing a data quality issue, or improving an existing workflow.

You take ownership of your work, communicate technical decisions clearly, and collaborate comfortably across global teams. You think beyond the initial implementation, considering monitoring, maintainability, security, and the needs of the people who rely on the data.

Does this sound like you?

• Have you designed and supported scalable data pipelines? What challenges did you solve?
• How have you used SQL and Python to build or optimize data solutions?
• Which AWS data services have you used, and how did they fit together?
• What is your experience with Apache Spark or PySpark for processing large datasets?
• How do you monitor pipelines, investigate failures, and prevent recurring issues?
• How do you ensure data quality, integrity, security, and governance throughout a pipeline?
• Have you contributed to a Data Lake, Data Warehouse, or cloud migration initiative?
• How have you used orchestration, automation, CI/CD, or DataOps to improve reliability?
• Are you comfortable discussing technical requirements and troubleshooting with international teams in English at C2 level?
• Have you worked in Financial Services or another regulated environment?

#EY BR