Data Engineer Sênior
J
JobgetherIT Security
BrazilFull-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- PythonApache AirflowGCPGitData engineeringdbt
Requirements
- Strong professional experience in data engineering and building data pipelines.
- Hands-on experience with Google Cloud services, particularly Dataflow, Dataproc, Cloud Run, Google Workflows, and Google Scheduler.
- Solid experience with data transformation and modeling tools such as Dataform and dbt.
- Strong knowledge of Apache Airflow for workflow orchestration.
- Proficiency in Python for data engineering and automation.
- Experience using Git for version control and collaborative software development.
- Understanding of data architecture, governance, and engineering principles.
- Ability to work with modern cloud-based data processing environments and automation practices.
- Strong analytical and problem-solving skills with attention to data quality and reliability.
- Ability to collaborate effectively with technical teams and contribute to complex digital transformation initiatives.
- Proactive mindset, ownership, and commitment to continuous learning and technical improvement.
Responsibilities
- Design and implement data pipelines that extract, process, standardize, store, and distribute data efficiently.
- Apply established data architecture and governance principles throughout the data engineering lifecycle.
- Develop and maintain data processing solutions using Google Cloud services such as Dataflow, Dataproc, Cloud Run, Google Workflows, and Google Scheduler.
- Build and maintain data transformation workflows using Dataform and dbt.
- Develop data engineering applications and automation using Python.
- Orchestrate data workflows and pipelines using Apache Airflow.
- Apply version control and collaborative development practices using Git.
- Support the automation and optimization of data processing and engineering workflows.
- Contribute to the reliability, scalability, maintainability, and quality of modern data solutions.
- Collaborate with technical teams to continuously improve data engineering practices and deliver solutions aligned with business needs.
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