Company
Technology
EngenheirodeDadosPlenoGCP/DBT
Neural analysis suggests this role is
optimal for Mid candidates.
“Engenheiro de Dados Pleno GCP/DBT. Skills: Data Engineering, Google Cloud Platform, DBT, BigQuery. Analyze existing data warehouse architectures. Analyze data sources”
Industry & Context.
Analytical thinking; Problem-solving capabilities
What They're Looking For.
Must Have
3 years of hands-on experience working with DBT in production, Expertise in DBT concepts, Solid understanding of layered data architecture approaches, Advanced experience with Google Cloud Platform services, Knowledge of data modeling, query optimization, partitioning, clustering, data ingestion, governance, and security best practices within BigQuery, Experience managing cloud storage environments, access controls, lifecycle policies, and secure data operations, Proficiency in Python, PySpark, and advanced SQL, Familiarity with Shell Scripting, Experience with Git-based version control systems, Understanding of networking, cloud security, VPCs, firewall configurations, and access management principles, Analytical thinking, Problem-solving capabilities, Ability to collaborate in distributed teams, Experience working within Agile environments, Using Jira for project tracking
Nice to Have
GCP certifications, AWS certifications, Azure certifications
What You'll Do.
Analyze existing data warehouse architectures
Analyze business requirements
Define scalable cloud data solutions
Design data architectures using Google Cloud Platform services
Implement data architectures using Google Cloud Platform services
Develop ELT/ETL pipelines using DBT
Maintain ELT/ETL pipelines using DBT
Optimize ELT/ETL pipelines using DBT
Create efficient data models
Create scalable data models
Align data models with modern data warehouse best
Define data migration strategies
Execute data migration strategies
Implement data validation
Implement data monitoring
Implement data quality controls
Ensure reliability across data pipelines
Ensure consistency across data pipelines
Optimize query performance
Optimize resource utilization
Optimize cloud infrastructure costs
Maintain operational efficiency
Apply data governance policies
Apply data security policies
Apply access control policies
Protect sensitive information
Troubleshoot performance issues
Troubleshoot operational issues
Troubleshoot data-related issues
Produce technical documentation
Maintain technical documentation
Collaborate effectively with stakeholders
Collaborate effectively with technical teams
Collaborate effectively with business areas
Support Agile methodologies
Support project management practices
How You'll Work.
Team & Collaboration
Distributed teams; Agile methodologies; Project management practices
Process & Methodology
Agile, Jira
Full Job Description
## Accountabilities Analyze existing data warehouse architectures, data sources, and business requirements to define scalable cloud data solutions. Design and implement data architectures using Google Cloud Platform services, including data storage, processing, orchestration, and analytics components. Develop, maintain, and optimize ELT/ETL pipelines using DBT, BigQuery, Dataproc, Dataflow, and related technologies. Create efficient and scalable data models, including staging, transformation, and data mart layers aligned with modern data warehouse best practices. Define and execute data migration strategies, including full loads, incremental loads, and change data capture approaches. Implement data validation, monitoring, and quality controls to ensure reliability and consistency across data pipelines. Optimize query performance, resource utilization, and cloud infrastructure costs while maintaining scalability and operational efficiency. Apply data governance, security, and access control policies to ensure compliance and protect sensitive information. Troubleshoot and resolve performance, operational, and data-related issues across cloud environments and pipelines. Produce and maintain comprehensive technical documentation covering architecture, processes, pipelines, and operational procedures. Collaborate effectively with stakeholders, technical teams, and business areas while supporting Agile methodologies and project management practices. Requirements Minimum of 3 years of hands-on experience working with DBT in production environments. Strong expertise in DBT concepts, including models (staging, intermediate, marts), ref(), source(), macros (Jinja), seeds, snapshots, and testing frameworks. Solid understanding of layered data architecture approaches such as Staging, Transformation, and Data Mart/Data Warehouse models. Advanced experience with Google Cloud Platform services, especially BigQuery, Cloud Storage, Dataproc, Dataflow, Composer, and IAM. Strong knowl
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