Data Engineer (Alteryx | AWS) | PL
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Data Engineer (Alteryx | AWS) | PL
Location
Brazil
Experience
Mid
Posted
Jul 14, 2026
Apply by
August 13, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Home
Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer (Alteryx | AWS) | PL based in Brazil.
This role offers the opportunity to work on modern data engineering initiatives focused on cloud migration, scalability, and data transformation.
You will contribute to the evolution of data platforms by migrating existing workflows into cloud-native architectures.
The position combines hands-on engineering with data architecture practices, supporting reliable and high-performance data ecosystems.
You will work with advanced technologies across AWS, distributed processing, and Data Mesh environments.
The ideal candidate is passionate about building efficient pipelines, improving data quality, and solving complex technical challenges.
This is a remote opportunity for a data professional who wants to contribute to innovative projects involving modern analytics and cloud technologies.
### Accountabilities:
The Data Engineer will be responsible for designing, improving, and migrating scalable data solutions while ensuring reliability, performance, and governance across modern data environments.
- Maintain scalable and reliable data pipelines using modern distributed processing technologies to support data ingestion, transformation, and availability.
- Migrate existing workflows and code developed in Alteryx to AWS-based solutions, leveraging services such as AWS Glue.
- Analyze, rewrite, and restructure existing programs to align with cloud-native development standards and data platform requirements.
- Rebuild data pipelines to improve performance, scalability, maintainability, and governance.
- Migrate workflows into a Data Mesh ecosystem and ensure proper integration with data domains.
- Support orchestration and integration processes across data platforms and services.
- Develop solutions following best practices for data engineering, architecture, and operational reliability.
- Collaborate with technical teams to optimize data processing and improve platform capabilities.
## Requirements:
The ideal candidate will have experience in data engineering, cloud platforms, and modern data architectures, with the ability to design and implement scalable solutions.
- Professional experience working with data engineering projects and pipeline development.
- Experience with Apache Spark, Apache Airflow, Apache Kafka, and dbt.
- Strong knowledge of SQL and NoSQL databases, including technologies such as PostgreSQL, MongoDB, and Cassandra.
- Experience with cloud data platforms, including AWS Glue, Databricks, and BigQuery.
- Experience implementing Data Lake and Data Lakehouse architectures.
- Understanding of data governance, scalability, performance optimization, and cloud-based data processing.
- Ability to analyze existing solutions and adapt them to modern engineering standards.
- Strong problem-solving skills and ability to collaborate in technical environments.
- Familiarity with Data Mesh concepts and distributed data architectures is a plus.
## Benefits:
- Fully remote work model.
- Opportunity to work with modern cloud technologies and advanced data platforms.
- Exposure to large-scale data engineering projects and innovative architectures.
- Opportunity to develop expertise in AWS, Data Mesh, and cloud-native solutions.
- Collaborative environment focused on technology, innovation, and continuous learning.
- Professional growth opportunities through challenging technical projects.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
[Why Apply Through Jobgether?](https://jobgether.com/how-jobgether-works)
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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Key Responsibilities
- Maintain scalable and reliable data pipelines using distributed processing technologies.
- Migrate existing workflows and code from Alteryx to AWS-based solutions leveraging AWS Glue.
- Analyze, rewrite, and restructure existing programs to align with cloud-native development standards.
- Rebuild data pipelines to improve performance, scalability, maintainability, and governance.
- Migrate workflows into a Data Mesh ecosystem and ensure proper integration with data domains.
- Support orchestration and integration processes across data platforms and services.
- Develop solutions following best practices for data engineering, architecture, and operational reliability.
- Collaborate with technical teams to optimize data processing and improve platform capabilities.
Skills Required
AWSAlteryxApache SparkApache AirflowApache KafkadbtSQLNoSQLPostgreSQLMongoDBCassandraAWS GlueDatabricksBigQueryData LakeData LakehouseProblem solvingCollaborationData MeshDistributed data architectures
Benefits
- Fully remote work model
- Opportunity to work with modern cloud technologies
- Exposure to large-scale data engineering projects
- Professional growth opportunities
- Collaborative environment
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