Data Engineer (Python/AWS/Snowflake)

Role overview

Design, build, and operate a cloud data platform using AWS serverless services and Apache Airflow. The work spans data engineering, quality, and governance, with an emphasis on dependable pipelines, automated delivery, traceable data, and efficient cloud use. The role calls for technical autonomy in choosing architecture and setting platform practices.

Responsibilities - Build and run AWS data platform components, selecting services to fit use cases, cost, and operational needs. - Develop Airflow workflows with reliable retries, idempotent execution, service level targets, and failure handling. - Configure and operate managed Airflow environments, including dependencies, plugins, worker scaling, and blue-green deployments. - Orchestrate data processing jobs and automate deployments through CI/CD. - Improve data quality, governance, lineage, and availability so business users can rely on timely, consistent data. - Make architecture decisions and define good engineering practices across the platform.

Requirements - Senior data engineering experience, including hands-on work with Python, AWS, and Snowflake, as reflected in the role title and description. - Practical experience building and operating AWS serverless data platforms. - Experience developing Airflow DAGs and managing a production Airflow environment. - Ability to design reliable pipelines and automate infrastructure or delivery workflows. - Sound judgment in balancing platform reliability, operational needs, and cloud costs.

Benefits and work setup - Full-time, remote role based in Argentina. - The role requires dedicated focus during agreed working hours; additional professional work must be disclosed and must not interfere with responsibilities.