About the role
We are seeking a skilled Data Engineer with strong expertise in Snowflake and dbt (Data Build Tool) to design, build, and optimize scalable data pipelines. The role involves working on modern data platforms, enabling analytics, reporting, and advanced data transformations across cloud or hybrid environments.
Responsibilities:
- Develop and maintain scalable data pipelines and transformation workflows using Snowflake and dbt.
- Build, optimize, and maintain dbt models, macros, tests, snapshots, and documentation.
- Write complex SQL queries for data transformation, validation, and analysis.
- Work with GitHub for source control, branching, pull requests, and code reviews.
- Develop and maintain GitHub Actions/CI-CD workflows for automated testing and deployment of data projects.
- Integrate data from REST APIs and external data sources, including authentication, pagination, error handling, and JSON processing.
- Collaborate with engineering, analytics, and business teams to understand data requirements and deliver reliable datasets.
- Implement data-quality checks and monitoring to ensure accuracy and consistency.
- Troubleshoot pipeline, transformation, and deployment issues.
- Contribute to improving data engineering standards, automation, documentation, and development practices.
Requirements:
- Core Technologies: Snowflake, GitHub, GitHub Actions/Workflows, and DBT (Data Build Tool); models, macros, testing, documentation, API exp preferred, and Node.js would be advantageous.
- Data Engineering Concepts: Data modeling (dimensional modeling, star/snowflake schemas), ETL vs ELT architecture, data warehousing and lakehouse architecture, Pipeline performance tuning and optimization.