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This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer (GCP Cloud) based in Brazil.
This role is focused on designing, building, and scaling modern data pipelines in a cloud-native environment, enabling high-performance analytics and data-driven decision-making across the organization. You will play a key role in developing robust data architectures that support large-scale processing, ensuring reliability, efficiency, and governance across data workflows. Working within a collaborative Data & AI ecosystem, you will contribute to the evolution of end-to-end data platforms leveraging Google Cloud technologies. The position involves close interaction with analytics, engineering, and business teams to translate requirements into scalable technical solutions. You will work on mission-critical pipelines that process high volumes of data and directly support strategic business outcomes. This is a highly technical role that blends software engineering, data architecture, and cloud infrastructure expertise.
Accountabilities:
You will be responsible for building and optimizing scalable data pipelines and cloud-based data solutions, ensuring high availability, performance, and reliability across all data assets. Your work will directly support analytics, machine learning, and business intelligence initiatives in a modern cloud environment.
- Design, develop, and maintain scalable data pipelines in cloud environments
- Implement distributed data processing solutions using Apache Beam
- Orchestrate data workflows and pipelines using Apache Airflow
- Develop robust Python-based data engineering solutions following best practices
- Work within Google Cloud Platform (GCP) leveraging services such as BigQuery, Cloud Storage, and Cloud Composer
- Build and maintain CI/CD pipelines for data workflows and deployments
- Use YAML/YML configurations to support automation and infrastructure standardization
- Containerize applications and services using Docker
- Develop, test, and document data transformation models using dbt
- Optimize and manage analytical workloads using BigQuery
- Collaborate with engineering, analytics, and business teams to ensure data quality and performance
- Support architectural decisions related to scalability, observability, and data governance
Requirements:
This role requires strong technical expertise in cloud data engineering, distributed processing, and modern data stack tools, along with the ability to work in complex, high-volume environments. English proficiency is essential due to international collaboration.
- Advanced English (mandatory), required for meetings, documentation, and stakeholder communication
- Proven experience working with Google Cloud Platform (GCP) in data engineering contexts
- Hands-on experience with BigQuery, Cloud Storage, Cloud Composer, and/or Dataflow
- Strong proficiency in Python for data engineering and backend development
- Experience with Apache Beam for distributed data processing
- Experience with Apache Airflow for workflow orchestration
- Solid understanding of CI/CD practices for data pipelines
- Experience working with YAML/YML configurations
- Familiarity with Docker for containerization
- Hands-on experience with dbt for data transformation and modeling
- Strong knowledge of version control, testing, documentation, and software engineering best practices
Nice to have:
- Experience in consulting or client-facing project environments
- Knowledge of Lakehouse, Data Lake, or Data Warehouse architectures
- Experience with additional GCP services such as Dataproc and Looker
- Familiarity with data observability, monitoring, and data quality practices
- Experience working with high-volume, production-grade data systems
- Google Cloud certifications in Data Engineering
Benefits:
- Remote-first role based in Brazil
- Opportunity to work on large-scale Data & AI projects
- Exposure to modern cloud-native data engineering stack (GCP ecosystem)
- Strong culture of learning, knowledge sharing, and professional development
- Collaborative environment with cross-functional engineering and analytics teams
- Participation in innovative projects with real business impact
- Access to continuous technical growth and cloud certification support
- Inclusive and diverse workplace with strong emphasis on community and collaboration.
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