Data Engineer (Tech-lead)
New
J
JobgetherData Engineering
Brazil, Overlap with Central Time (CST/CDT)ContractLead
Salary not disclosed
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Job Details
- Languages
- Fluent English
- Required Skills
- DockerPythonSQLApache AirflowBashKubernetesSnowflakedbt
Requirements
- Advanced proficiency in Python, SQL, and Bash.
- Deep hands-on experience with Snowflake as a primary cloud data warehouse.
- Strong experience with dbt for data modeling, transformation, testing, and maintainable analytics engineering workflows.
- Practical expertise with Apache Airflow for designing, orchestrating, monitoring, and troubleshooting complex data workflows.
- Solid DevOps experience with Docker, Kubernetes, and GitLab CI/CD.
- Proven experience in data system architecture, with the ability to design scalable and production-ready data ecosystems.
- Previous experience leading or managing technical teams, providing mentorship and establishing engineering best practices.
- Strong understanding of the complete data product lifecycle.
- Excellent analytical and problem-solving abilities.
- Strong communication and collaboration skills.
- Fluent English, with excellent written and verbal communication skills.
Responsibilities
- Design and architect scalable, reliable, and high-quality data systems and end-to-end pipelines following modern engineering standards and best practices.
- Lead the development of complex data models and transformation workflows using Snowflake and dbt.
- Design, implement, and optimize Apache Airflow workflows to orchestrate sophisticated data pipelines and manage complex dependencies.
- Establish reliable infrastructure and deployment practices using Docker, Kubernetes, and GitLab CI/CD.
- Take ownership of the complete data product lifecycle, from architecture and initial development through deployment, production operation, and continuous improvement.
- Develop and maintain robust data processing and automation solutions using Python, SQL, and Bash.
- Provide technical leadership, mentorship, and guidance to engineering team members.
- Drive technical decision-making around architecture, scalability, reliability, maintainability, and production readiness.
- Collaborate closely with distributed technical and product teams to translate requirements into effective data solutions.
- Ensure data systems and products are delivered efficiently, reliably, and in alignment with broader project objectives.
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