Data Engineer – Data Pipelines, Modeling

🕒 May 8

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Ryz Labs

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11 - 50 employees

Ryz Labs builds startups from the ground-up and helps other startups scale by providing top-tier technical talent solutions.

📋 Description

• 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

🎯 Requirements

• dbt: Hands-on experience developing dbt models at scale, including use of macros, snapshots, testing frameworks, and documentation. Familiarity with dbt Cloud or CLI workflows • Snowflake: Strong SQL skills and understanding of Snowflake architecture, including query performance tuning, cost optimization, and use of semi-structured data • Airflow: Solid experience managing Airflow DAGs, scheduling jobs, and implementing retry logic and failure handling; familiarity with Astronomer is a plus • Data Modeling: Proficient in dimensional modeling and building reusable data marts that support analytics and operational use cases