Cloud Data Engineer

remoting.work; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

remoting.work is seeking a Cloud Data Engineer to design and maintain scalable data pipelines in a cloud environment. You will develop ETL processes using Spark and orchestrate with Airflow while ensuring high data quality and availability. This remote role is aligned with US time zones.

The role emphasizes hands-on work with cloud databases and orchestrating workflows across AWS Glue, Azure Data Factory, and Spark, with strong English communication documented across the team.

Qualifications

• Experience building ETL pipelines and data integration.
• Hands-on experience with cloud databases and data pipeline development.
• Experience with AWS Glue, Airflow, Azure Data Factory, and Spark.
• Excellent written English.

Responsibilities

• Design and maintain data pipelines that move and transform data across cloud systems.
• Develop and manage extract, transform, and load processes using Apache Spark and Airflow.
• Build and optimize cloud database structures to support scalable data storage.
• Orchestrate and schedule data workflows using Airflow, AWS Glue, and Azure Data Factory.
• Monitor data pipeline performance and resolve issues to maintain data accuracy.

Skills

Data management

ETL pipelines

English proficiency

Tools

AWS Glue

Airflow

Azure Data Factory

Apache Spark

Job description

Cloud Data Engineer

Remote (Based at an approved local secure facility). We work US time zones and ask that you're available during those hours, even if that means adjusting your schedule.

About The Role

This role exists to ensure reliable, accurate, and timely data availability across the organization. You will build and maintain cloud-based data pipelines that support informed, data-driven decisions. The work is primarily asynchronous, with clear documentation replacing constant live coordination. Our team is distributed across multiple countries and time zones, working within structured processes to maintain consistent data quality.

What You'll Do

• Design and maintain data pipelines that move and transform data across cloud systems
• Develop and manage extract, transform, and load processes using Apache Spark and Airflow
• Build and optimize cloud database structures to support scalable data storage
• Orchestrate and schedule data workflows using Airflow, AWS Glue, and Azure Data Factory
• Monitor data pipeline performance and resolve issues to maintain data accuracy

What We're Looking For

• Proven experience in data management and building extract, transform, and load processes
• Hands‑on experience with cloud databases and data pipeline development
• Working knowledge of AWS Glue, Airflow, Azure Data Factory, and Apache Spark
• Strong written English — our company works in English