Data Engineer – Data Pipelines

3 semanas atrás

Buenos Aires, Brasil Ryz Labs Tempo inteiro

Join to apply for the Data Engineer – Data Pipelines & Modeling role at Ryz Labs .

This position is only for professionals based in Argentina or Uruguay.

We're looking for a data engineer to help enhance and scale the data transformation and modeling layer. The role focuses on building robust, maintainable pipelines using dbt, Snowflake, and Airflow to support analytics and downstream applications. You will work closely with data, analytics, and software engineering teams to create scalable data models, improve pipeline orchestration, and ensure high-quality data delivery.

Key Responsibilities:
  • 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 for business reporting, lifecycle marketing, and experimentation.
  • 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 and efficient dependency management.
  • Collaborate on data model design best practices, including dimensional modeling, naming conventions, and versioning strategies.
Core Skills & Experience:
  • Hands-on experience developing dbt models at scale, including macros, snapshots, testing frameworks, and documentation. Familiarity with dbt Cloud or CLI workflows.
  • Strong SQL skills and understanding of Snowflake architecture, including query performance tuning and cost optimization.
  • Experience managing Airflow DAGs, scheduling jobs, and handling retries and failures; familiarity with Astronomer is a plus.
  • Proficiency in dimensional data modeling and building reusable data marts.
  • Familiarity with AWS services such as DMS, Kinesis, and Firehose is a plus.
  • Familiarity with event data and flows, especially related to Segment, is a plus.
Additional Information:
  • Seniority level: Not Applicable
  • Employment type: Full-time
  • Job function: Information Technology
  • Industries: Technology, Information and Internet
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