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Airflow Developer Jobs (NOW HIRING)

LTM

Senior Data Platform / Airflow Engineer

Plano, TX

$101K - $138K/yr

Design, build, and operate large-scale data platforms powered by Apache Airflow * Manage and optimize hundreds to thousands of DAGs with high task throughput * Drive platform reliability, scalability ...

IDC Technologies

Data Engineer in Sunnyvale CA

Sunnyvale, CA · On-site

$134K - $161K/yr

Should be familiar with modern data platforms like Apache Presto or AWS Athena, and workflow tools like Apache Airflow. Engineers will write data collection scripts, aggregation algorithms, and ...

ConnectedX Inc

Senior DATA ENGINEER

Plano, TX

$101K - $138K/yr

Hadoop, Spark, Athena, materialized views DevOps Tools: Docker, Kubernetes, Jenkins, Terraform, Git, Big query, Firebase Workflow Orchestration: Apache Airflow Programming Languages: Python, SQL ...

ConnectedX Inc

Senior DATA ENGINEER

Murphy, TX

$101K - $137K/yr

Hadoop, Spark, Athena, materialized views DevOps Tools: Docker, Kubernetes, Jenkins, Terraform, Git, Big query, Firebase Workflow Orchestration: Apache Airflow Programming Languages: Python, SQL ...

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How much do airflow developer jobs pay per hour?

As of Jun 12, 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 the salary of Airflow developer?

The salary of an Airflow developer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and the complexity of projects. Skilled developers with expertise in Python, cloud platforms, and data pipeline management tend to earn higher salaries.

What are Airflow Developers?

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 is an Airflow developer?

An Airflow developer is a software professional who designs, builds, and maintains data workflows using Apache Airflow. They typically have skills in Python, data engineering, and workflow orchestration, and work to automate and schedule complex data pipelines in cloud or on-premises environments.

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.

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.

Is Airflow in demand?

Airflow developers are in high demand due to the increasing need for data pipeline orchestration in data engineering and analytics. Skills in Python, cloud platforms, and workflow management tools contribute to job opportunities across various industries.

What jobs in the US pay 300,000 a year?

For an Airflow Developer, earning $300,000 annually typically requires senior-level experience, specialized skills in data pipeline orchestration, and often working in large organizations or consulting roles. High salaries are common in roles involving complex data infrastructure, cloud platforms, and leadership responsibilities. Certifications like Apache Airflow or cloud provider credentials can also contribute to higher compensation.
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Airflow Developer jobs near you
Infographic showing various Airflow Developer job openings in the United States as of June 2026, with employment types broken down into 2% Internship, 73% Full Time, 19% Part Time, 2% Temporary, and 4% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $109,905 per year, or $52.8 per hour.

Senior Airflow Engineer / Data Orchestration Specialist

Purple Drive Technologies

Phoenix, AZ • On-site

$105K - $143K/yr

Full-time

Posted 20 days ago

Job description

Overview:
Job Title: Airflow Engineer - Data Pipeline Automation
Location: Phoenix, AZ (Onsite | Contract)
Employment Type: Contract
Job Summary
We are seeking a highly skilled Airflow Engineer with expertise in designing, optimizing, and maintaining large-scale data workflows. The ideal candidate will have deep knowledge of Airflow architecture, DAG development, CI/CD pipeline management, and cloud integrations (Azure/AWS). This is an onsite contract role in Phoenix, AZ.
Key Responsibilities
  • Airflow Architecture: Design, configure, and optimize Airflow environments, including schedulers, executors (Celery, Kubernetes), and plugins.
  • DAG Development: Build complex, modular, and reusable DAGs to automate data pipelines and workflows.
  • Performance Optimization: Identify bottlenecks and implement orchestration and scheduling best practices.
  • Cloud Integration: Connect Airflow with Azure Data Factory, Databricks, Azure Storage, AWS, and other cloud-native services.
  • CI/CD Management: Develop and maintain CI/CD pipelines for DAG deployment, testing, and version control using Azure DevOps or similar tools.
  • Monitoring & Alerting: Implement logging, monitoring, and alerting frameworks for Airflow jobs to ensure reliability.
  • Documentation & Mentoring: Maintain technical documentation and conduct knowledge-sharing/mentorship sessions with teams.
  • Troubleshooting: Provide expert-level support for Airflow-related incidents and contribute to root cause analysis.
Required Skills
  • Strong expertise in Apache Airflow (architecture, schedulers, executors, plugins).
  • Proficiency in Python (must) and Java (nice to have) for DAG and pipeline development.
  • Hands-on experience with cloud platforms (Azure, AWS) - Data Factory, Databricks, Synapse, Functions, Storage.
  • Familiarity with CI/CD tools (Azure DevOps, Jenkins, GitLab CI/CD).
  • Experience with Docker and Kubernetes for containerized Airflow deployments.
  • Strong troubleshooting, debugging, and performance optimization skills.
  • Excellent communication and collaboration skills.

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