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.
- ️ 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.
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
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Design, develop, maintain, and optimize scalable, reliable data pipelines.
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Build data ingestion, integration, and transformation processes using SQL, Python, and distributed processing technologies.
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Develop and support AWS solutions using Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, and AWS Lambda.
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Contribute to the development and evolution of Data Lakes, Data Warehouses, and modern data platforms.
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Implement ETL and ELT processes aligned with technical requirements and business needs.
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Process large data volumes using Apache Spark or PySpark.
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Contribute to architecture discussions, helping shape secure, scalable, and maintainable solutions.
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Monitor and optimize pipelines, queries, transformations, and cloud workloads.
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Troubleshoot data ingestion, processing, storage, and delivery issues, conducting root cause analysis and implementing lasting fixes.
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Embed data quality, integrity, security, and governance into engineering processes.
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Collaborate with architects, software engineers, analysts, and business stakeholders throughout delivery.
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Support cloud migrations and data platform modernization initiatives.
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Implement automation, version control, CI/CD, and DataOps practices.
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Maintain technical documentation, data flows, and operational procedures while ensuring alignment with technical standards, internal controls, and applicable regulatory requirements.
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Share knowledge and contribute to standardization and continuous improvement.
What you bring
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A bachelor’s degree in Computer Science, Software Engineering, or a related field.
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English proficiency at C2 level, with the ability to communicate effectively in an international environment.
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Experience designing, developing, and supporting scalable data pipelines.
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Advanced SQL and Python skills.
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Experience with ETL, ELT, data ingestion, integration, and transformation.
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Experience with AWS data services, including Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, and AWS Lambda.
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Knowledge of data modeling, Data Warehouse architectures, and Data Lakes.
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Experience with distributed processing using Apache Spark or PySpark.
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The ability to develop, monitor, optimize, and troubleshoot data pipelines.
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Knowledge of data quality, security, and governance practices.
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Experience working in Agile environments with multidisciplinary and distributed teams.
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Strong analytical skills, autonomy, clear communication, and a commitment to delivery quality.
Experience that will help you stand out
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Databricks or Snowflake.
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Apache Airflow or equivalent orchestration tools.
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dbt.
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Kafka or other messaging and streaming technologies.
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Terraform and Infrastructure as Code.
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Git, automation, and CI/CD pipelines.
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DataOps practices.
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Data platform migration, modernization, or transformation projects.
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Financial institutions, Banking, Wealth Management, Asset Management, or other regulated environments.
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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?
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Have you designed and supported scalable data pipelines? What challenges did you solve?
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How have you used SQL and Python to build or optimize data solutions?
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Which AWS data services have you used, and how did they fit together?
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What is your experience with Apache Spark or PySpark for processing large datasets?
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How do you monitor pipelines, investigate failures, and prevent recurring issues?
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How do you ensure data quality, integrity, security, and governance throughout a pipeline?
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Have you contributed to a Data Lake, Data Warehouse, or cloud migration initiative?
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How have you used orchestration, automation, CI/CD, or DataOps to improve reliability?
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Are you comfortable discussing technical requirements and troubleshooting with international teams in English at C2 level?
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Have you worked in Financial Services or another regulated environment?
Interested in applying?
Please share your updated resume, location in Brazil, preferred work model, current compensation, and compensation expectations. Specify the currency and whether the amounts are monthly or annual.
Highlight relevant AWS projects, the pipelines you built or improved, and measurable results such as faster processing, improved reliability, or better data quality.
Resume keywords
Senior Data Engineer, Data Engineering, AWS, Cloud Data Platforms, Data Pipelines, Scalable Data Pipelines, SQL, Advanced SQL, Python, ETL, ELT, Data Ingestion, Data Integration, Data Transformation, Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, AWS Lambda, Data Modeling, Data Warehouse, Data Lake, Apache Spark, PySpark, Distributed Processing, Pipeline Monitoring, Performance Optimization, Troubleshooting, Root Cause Analysis, Data Quality, Data Integrity, Data Security, Data Governance, Cloud Migration, Data Platform Modernization, Databricks, Snowflake, Apache Airflow, Data Orchestration, dbt, Kafka, Data Streaming, Terraform, Infrastructure as Code, Git, Version Control, Automation, CI/CD, DataOps, Agile, Distributed Teams, Technical Documentation, Regulatory Compliance, Financial Services, Banking, Wealth Management, Asset Management, English C2, AWS Certifications, Azure Certifications, Databricks Certifications, Snowflake Certifications
#EY BR