Snowflake Data Engineer (Airflow)

Quick Facts

• Role: Snowflake Data Engineer (Airflow)

Description

Develop and maintain data pipelines using Apache Airflow and Python that ingest data from APIs, databases, and file-based sources into AWS S3 and Snowflake. Build dbt-based transformations, optimize Snowflake query/warehouse performance, and implement monitoring, error handling, alerting, and automated data quality validation. Maintain technical documentation and follow data engineering best practices.

Responsibilities

• Develop and maintain data pipelines with Apache Airflow and Python

• Ingest data from APIs, databases, and files into AWS S3 and Snowflake

• Design and implement transformations using dbt

• Optimize Snowflake queries, warehouse performance, and resource consumption

• Implement monitoring, error handling, and alerting

• Ensure data quality, consistency, and reliability via automated testing and validation

• Maintain technical documentation and engineering best practices

Requirements

• 3+ years of professional Data Engineering experience

• Strong Apache Airflow expertise (DAG development, operators, sensors, hooks, TaskFlow API, workflow optimization)

• Advanced Python skills (clean, maintainable, testable code)

• Advanced SQL knowledge (complex queries, CTEs, window functions, performance optimization)

• Hands-on Snowflake experience (warehouses, stages, external volumes, data loading)

• Practical dbt knowledge (models, tests, macros, snapshots, incremental transformations)

• AWS S3 and Data Lake architecture experience (partitioning, file formats, access management)

• Git and CI/CD familiarity

• English proficiency at B2 level or higher

Benefits

Not specified in the provided posting.