Data Engineer: Build Scalable Pipelines with dbt, Snowflake

Ryz Labs; Municipio de Esquel; Presencial; ARS 89.781.382 - 164.599.200; Jornada completa

Descripción de la vacante

Ryz Labs is seeking a data engineer based in Latam to help scale our data transformation and modeling layer. You will build robust pipelines using dbt, Snowflake, and Airflow to support analytics and downstream applications.

You’ll work closely with the data, analytics, and software engineering teams to create scalable data models, improve pipeline orchestration, and ensure trusted, high-quality data delivery.

Formación

• Hands-on experience developing dbt models at scale with macros, snapshots, tests and docs.
• Strong SQL skills and understanding of Snowflake architecture and performance.
• Solid experience with data modeling and building reusable data marts for analytics.
• Familiarity with dbt Cloud or CLI workflows and test coverage.
• Experience with Shopify in data integration contexts.

Responsabilidades

• Design, implement, and optimize data pipelines that extract, transform, and load data into Snowflake from multiple sources using Airflow and AWS services
• Build modular, well-documented dbt models with strong test coverage to serve business reporting, lifecycle marketing, and experimentation use cases
• Partner with analytics and business stakeholders to define source-to-target transformations and implement them in dbt
• Maintain and improve our orchestration layer (Airflow/Astronomer) to ensure reliability, visibility, and efficient dependency management
• Collaborate on data model design best practices, including dimensional modeling, naming conventions, and versioning strategies

Conocimientos

dbt

Snowflake

Airflow

Data modeling

Shopify

Herramientas

dbt Cloud/CLI

Astronomer

Airflow

Descripción del empleo

Ryz Labs is seeking a data engineer based in Latam to help scale our data transformation and modeling layer. You will build robust pipelines using dbt, Snowflake, and Airflow to support analytics and downstream applications.

You’ll work closely with the data, analytics, and software engineering teams to create scalable data models, improve pipeline orchestration, and ensure trusted, high-quality data delivery.