Engenheiro de Dados SR - cloud GCP in Brazil, Indiana at Jobgether
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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 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.
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
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
- 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.