Data Engineer (Python/AWS/Snowflake)

Darwoft; United States; Remote; USD 90,000 - 130,000; Full time

Benefits offered by this job

Remote role in Argentina

Job summary

Darwoft seeks a senior data engineer to design, build, and operate a data platform on AWS serverless services, orchestrated by Apache Airflow and managed as code. The role emphasizes dependable, traceable pipelines and timely data availability with autonomous architecture decisions.

The candidate will lead end-to-end Airflow DAGs, manage MWAA deployments, and implement data quality and governance practices while balancing reliability with cloud cost efficiency.

Qualifications

• Senior data engineering experience building and operating cloud data platforms.
• Strong experience with AWS serverless data services and Apache Airflow.
• Experience managing MWAA environments and their deployments and scaling.
• Ability to design reliable pipelines with retries, idempotency, and failure handling.
• Familiarity with infrastructure as code, CI/CD, data quality, and data governance.

Responsibilities

• Select suitable AWS serverless services based on use case, cost, and operational needs, and build and run the data platform.
• Develop end-to-end Airflow DAGs with attention to idempotency, retries, service-level objectives, and failure handling.
• Configure and operate managed Airflow environments, including dependencies, plugins, worker scaling, and blue/green deployments.
• Automate platform changes and releases through infrastructure as code and CI/CD.
• Establish practices for data quality, governance, consistency, and traceability.
• Balance reliability and timely delivery with cloud cost efficiency.

Skills

Senior data engineering

AWS serverless

Apache Airflow

MWAA

CI/CD

Infrastructure as code

Data governance

Tools

MWAA

Airflow

Job description

Role overview

Design, build, and operate a data platform on AWS serverless services, orchestrated with Apache Airflow and managed as code. The senior-level role combines data engineering with quality and governance, focusing on dependable, traceable pipelines, timely data availability, and efficient cloud use. It calls for technical autonomy in architecture decisions and platform practices.

Responsibilities

• Select suitable AWS serverless services based on use case, cost, and operational needs, and build and run the data platform.
• Develop end-to-end Airflow DAGs with attention to idempotency, retries, service-level objectives, and failure handling.
• Configure and operate managed Airflow environments, including dependencies, plugins, worker scaling, and blue/green deployments.
• Automate platform changes and releases through infrastructure as code and CI/CD.
• Establish practices for data quality, governance, consistency, and traceability.
• Balance reliability and timely delivery with cloud cost efficiency.

Requirements

• Senior data engineering experience building and operating cloud data platforms.
• Strong experience with AWS serverless data services and Apache Airflow.
• Experience managing MWAA environments and their deployments and scaling.
• Ability to design reliable pipelines with retries, idempotency, and failure handling.
• Familiarity with infrastructure as code, CI/CD, data quality, and data governance.
• Full-time availability in Argentina; additional professional work must be disclosed and must not interfere with role responsibilities.

Benefits and work setup

• Full-time employee role based remotely in Argentina.