O que a vaga pede
Job Title: Data Engineer
Location: Paulista Avenue, São Paulo
Work Mode: Hybrid, 3 days per week onsite
Employment Type: Full-Time Employee (CLT)
Primary Skills: SQL, Python, Snowflake
Experience: 7+ years
About the Role
We are looking for a Data Engineer with strong proficiency in SQL, Python, and Snowflake to work on large-scale data environments. The role involves developing and maintaining ELT/ETL pipelines, optimizing Snowflake objects and pipelines, supporting data-related automation, and working within Linux and containerized environments.
Requirements
- Strong proficiency in SQL, including complex queries, performance tuning, and data modeling.
- Hands-on experience with Snowflake, including schema design, optimization, warehousing best practices, and cost management.
- Experience refactoring and optimizing Snowflake objects and pipelines for large-scale data environments.
- Experience building and maintaining ELT/ETL pipelines using tools such as dbt, Apache Airflow, or similar.
- Familiarity with AWS data services including RDS, S3, Aurora, and backup/restore mechanisms.
- Working knowledge of Python for data pipeline scripting, automation, and tooling support.
- Proficiency with Git and GitHub for version control, branching workflows, pull requests, and collaborative development.
- Ability to work in Linux server environments, including file system navigation, shell scripting, and service management.
- Familiarity with containerization technologies such as Docker across cloud and local environments.
Responsibilities
- Build and maintain ELT/ETL pipelines.
- Refactor and optimize Snowflake objects and pipelines for large-scale data environments.
- Develop data pipeline scripting, automation, and tooling support using Python.
- Work with AWS data services including RDS, S3, Aurora, and backup/restore mechanisms.
- Manage development workflows using Git and GitHub.
- Work within Linux server environments and support shell scripting and service management.
- Work with Docker and containerized environments across cloud and local environments.