Data Engineer – Data Pipelines, Modeling

This is a fully remote position, open to applicants in Argentina.

📋 Description

• Design, develop, and enhance data pipelines that extract, transform, and load information into Snowflake from various sources utilizing Airflow and AWS services.

• Create modular and well-documented dbt models with comprehensive test coverage to support business reporting, lifecycle marketing, and experimentation needs.

• Collaborate with analytics and business stakeholders to specify source-to-target transformations and implement these in dbt.

• Sustain and enhance our orchestration layer (Airflow/Astronomer) to guarantee reliability, visibility, and effective dependency management.

• Work together on data model design best practices, encompassing dimensional modeling, naming conventions, and version control strategies.

⛳️ Requirements

• dbt: Practical experience in developing dbt models at scale, including the use of macros, snapshots, testing frameworks, and documentation. Familiarity with dbt Cloud or CLI workflows is beneficial.

• Snowflake: Strong SQL proficiency and a solid understanding of Snowflake architecture, including query performance tuning, cost optimization, and handling of semi-structured data.

• Airflow: Substantial experience in managing Airflow DAGs, scheduling tasks, and implementing retry logic and failure handling; experience with Astronomer is advantageous.

• Data Modeling: Expertise in dimensional modeling and constructing reusable data marts that support both analytics and operational use cases.

🏝️ Benefits

• Opportunity to work with cutting-edge technologies and tools in data engineering.

• Collaborative and inclusive work environment fostering professional growth.

• Competitive salary and comprehensive benefits package.