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Airflow Developer Jobs (NOW HIRING)

RAPID EAGLE INC

Python Developer

Charlotte, NC

$55 - $75/hr

Python Developer Onsite Role Charlotte NC Key Responsibilities * Build and maintain large-scale ... Develop and orchestrate ETL and ML pipelines with Apache Airflow, ensuring reliability, scalability ...

RAPID EAGLE INC

Python Developer

Charlotte, NC · On-site

$55 - $75/hr

Python Developer Onsite Role Charlotte NC Key Responsibilities * Build and maintain large-scale ... Develop and orchestrate ETL and ML pipelines with Apache Airflow, ensuring reliability, scalability ...

Xforia, Inc.

AWS Devops Engineer

Burbank, CA · On-site

$56.25 - $77/hr

Admin experience with Informatica PowerCenter or Developer. * Experience with Version Control ... Airflow -nice to have not a must.

Collabera

GIS - Analyst

Mossville, IL

Installing tools and job scheduling or data workflow tools like Crontab or Apache Airflow * Programming experience with one or more programming languages * Python, object oriented programming ...

System One

Data Engineer with DevOps

Dallas, TX · On-site

$52.25 - $71.50/hr

... DevOps Duration : Full Time Location : Pittsburgh, PA, Cleveland, OH, or Dallas, TX Work Mode : 5 ... Hands on experience with Apache Airflow for workflow orchestration (DAG design, scheduling ...

System One

Data Engineer with DevOps

Dallas, TX · On-site

$52.25 - $71.50/hr

... DevOps Duration : Full Time Location : Pittsburgh, PA, Cleveland, OH, or Dallas, TX Work Mode : 5 ... Hands on experience with Apache Airflow for workflow orchestration (DAG design, scheduling ...

System One

Data Engineer with DevOps

Dallas, TX · On-site

$52.25 - $71.50/hr

... DevOps Duration : Full Time Location : Pittsburgh, PA, Cleveland, OH, or Dallas, TX Work Mode : 5 ... Hands on experience with Apache Airflow for workflow orchestration (DAG design, scheduling ...

System One

Data Engineer with DevOps

Dallas, TX · On-site

$52.25 - $71.50/hr

... DevOps Duration : Full Time Location : Pittsburgh, PA, Cleveland, OH, or Dallas, TX Work Mode : 5 ... Hands on experience with Apache Airflow for workflow orchestration (DAG design, scheduling ...

System One

Data Engineer with DevOps

Dallas, TX · On-site

$52.25 - $71.50/hr

... DevOps Duration : Full Time Location : Pittsburgh, PA, Cleveland, OH, or Dallas, TX Work Mode : 5 ... Hands on experience with Apache Airflow for workflow orchestration (DAG design, scheduling ...

System One

Data Engineer with DevOps

Dallas, TX · On-site

$52.25 - $71.50/hr

... DevOps Duration : Full Time Location : Pittsburgh, PA, Cleveland, OH, or Dallas, TX Work Mode : 5 ... Hands on experience with Apache Airflow for workflow orchestration (DAG design, scheduling ...

System One

Data Engineer with DevOps

Dallas, TX · On-site

$52.25 - $71.50/hr

... DevOps Duration : Full Time Location : Pittsburgh, PA, Cleveland, OH, or Dallas, TX Work Mode : 5 ... Hands on experience with Apache Airflow for workflow orchestration (DAG design, scheduling ...

System One

Data Engineer with DevOps

Dallas, TX · On-site

$52.25 - $71.50/hr

... DevOps Duration : Full Time Location : Pittsburgh, PA, Cleveland, OH, or Dallas, TX Work Mode : 5 ... Hands on experience with Apache Airflow for workflow orchestration (DAG design, scheduling ...

System One

Data Engineer with DevOps

Dallas, TX · On-site

$52.25 - $71.50/hr

... DevOps Duration : Full Time Location : Pittsburgh, PA, Cleveland, OH, or Dallas, TX Work Mode : 5 ... Hands on experience with Apache Airflow for workflow orchestration (DAG design, scheduling ...

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Airflow Developer information

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How much do airflow developer jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for airflow developer in the United States is $52.84, according to ZipRecruiter salary data. Most workers in this role earn between $40.38 and $64.66 per hour, depending on experience, location, and employer.

What is an Airflow developer?

Airflow Developers are professionals who design, build, and maintain data workflows using Apache Airflow, an open-source platform for orchestrating complex computational workflows and data processing pipelines. They are responsible for writing, scheduling, and monitoring tasks (DAGs) that automate data movement and transformation across systems. Airflow Developers work closely with data engineers, analysts, and other stakeholders to ensure reliable and efficient data pipeline automation. Their expertise includes Python programming, Airflow configuration, troubleshooting, and best practices for scalable workflow management.

What are the key skills and qualifications needed to thrive as an Airflow developer, and why are they important?

To thrive as an Airflow Developer, you need strong programming skills in Python, experience with data pipelines, and a solid understanding of workflow orchestration concepts. Familiarity with Apache Airflow, cloud platforms (like AWS or GCP), and version control systems such as Git are typically required, along with knowledge of containerization tools like Docker. Analytical thinking, attention to detail, and effective communication are key soft skills for collaborating with data teams and troubleshooting complex workflows. These competencies ensure reliable, scalable, and maintainable data pipeline solutions that support organizational data needs.

What are some common challenges Airflow developers face when managing complex data pipelines, and how can these be addressed?

Airflow Developers often encounter challenges such as managing dependencies between tasks, handling large-scale workflows, and ensuring reliable pipeline execution. To address these, it's essential to design modular DAGs (Directed Acyclic Graphs), implement robust error handling, and use features like sensors and retries strategically. Collaboration with data engineers and stakeholders is also key for troubleshooting and optimizing workflows. Effective monitoring and logging practices further help in quickly identifying and resolving issues.

What is the difference between Airflow Developer vs Data Engineer?

AspectAirflow DeveloperData Engineer
Required CredentialsKnowledge of Apache Airflow, Python, SQLData modeling, SQL, Python, cloud platforms
Work EnvironmentFocus on workflow orchestration, automationData pipeline development, storage, processing
Industry UsageTech, finance, healthcare for workflow automationBroad industries for data infrastructure

While both roles involve working with data and Python, an Airflow Developer specializes in designing and maintaining workflow automation using Apache Airflow. In contrast, a Data Engineer builds and manages data pipelines and infrastructure across various tools and platforms. The roles often overlap but differ mainly in scope and focus.

Does Airflow require coding?

Airflow developers typically need to have programming skills in Python, as workflows are defined using code. Coding knowledge is essential for creating, maintaining, and troubleshooting data pipelines in Airflow.

Is Airflow part of DevOps?

An Airflow Developer works with Apache Airflow, a platform used to programmatically author, schedule, and monitor workflows. While Airflow is often employed within DevOps environments to automate data pipelines and deployment processes, it is not inherently part of DevOps but complements DevOps practices by enabling automation and orchestration. Knowledge of CI/CD tools and infrastructure management is beneficial for such roles.
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Airflow Developer jobs near you
Infographic showing various Airflow Developer job openings in the United States as of August 2026, with employment types broken down into 82% Full Time, 2% Part Time, and 16% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $109,905 per year, or $52.8 per hour.

System Administrator (GCP/AWS/Azure, PySpark, BigQuery, and Google Airflow)

MDAEdge

San Jose, CA • On-site

$65.25 - $86.50/hr

Full-time

Re-posted 23 days ago

Job description

Job Summary:
MDAEdge is a company focused on managing and optimizing Big Data environments. The role involves providing 24x7 support and optimizing data pipelines across cloud platforms such as Google Cloud, AWS, and Azure, with a strong emphasis on DevOps practices.
Responsibilities:
• Participate in 24x7x365 rotational shift support and operations for SAP environments.
• Serve as a team lead responsible for maintaining the upstream Big Data ecosystem, handling millions of financial transactions daily using PySpark, BigQuery, Dataproc, and Google Airflow.
• Streamline and optimize existing Big Data systems and pipelines while developing new ones, ensuring efficient and cost-effective performance.
• Manage the operations team during your designated shift and make necessary changes to the underlying infrastructure.
• Provide day-to-day support, improve platform functionality using DevOps practices, and collaborate with development teams to enhance database operations.
• Architect and optimize data warehouse solutions using BigQuery to enable efficient data storage and retrieval.
• Install, build, patch, upgrade, and configure Big Data applications.
• Administer and configure BigQuery environments, including datasets and tables.
• Ensure data integrity, availability, and security on the BigQuery platform.
• Implement partitioning and clustering strategies for optimized query performance.
• Define and enforce access policies for BigQuery datasets.
• Set up query usage caps and alerts to control costs and prevent overages.
• Troubleshoot issues in Linux-based systems with strong command-line proficiency.
• Create and maintain dashboards and reports to monitor key metrics such as cost and performance.
• Integrate BigQuery with other GCP services like Dataflow, Pub/Sub, and Cloud Storage.
• Enable BigQuery usage through tools such as Jupyter Notebook, Visual Studio Code, and CLI utilities.
• Implement data quality checks and validation processes to maintain data accuracy.
• Manage and monitor data pipelines using Airflow and CI/CD tools like Jenkins and Screwdriver.
• Collaborate with data analysts and scientists to gather data requirements and translate them into technical implementations.
• Provide guidance and support to application development teams for database design, deployment, and monitoring.
• Demonstrate proficiency in Unix/Linux fundamentals, scripting in Shell/Perl/Python, and using Ansible for automation.
• Contribute to disaster recovery planning and ensure high availability, including backup and restore operations.
• Experience with geo-redundant databases and Red Hat clustering is a plus.
• Ensure timely delivery within defined SLAs and project milestones, adhering to best practices for continuous improvement.
• Coordinate with support teams including DB, Google, PySpark data engineering, and infrastructure.
• Participate in Incident, Change, Release, and Problem Management processes.
Qualifications:
Required:
• 4–8 years of relevant experience.
• Strong experience with Big Data technologies including PySpark, BigQuery, and Google Airflow.
• Hands-on expertise in cloud platforms (Google Cloud, AWS, or Azure) and Linux system troubleshooting.
• Proficiency in automation and DevOps tools such as Shell/Python scripting, CI/CD processes, and Ansible.
Preferred:
• Experience with geo-redundant databases and Red Hat clustering is a plus.
Company:
The world doesn't have a talent shortage. It has a talent alignment problem. MDA Edge exists to fix that. Founded in , the company is headquartered in Sheridan, WY, US, , with a team of 51-200 employees. The company is currently Growth Stage.

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