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Airflow Developer Jobs in California (NOW HIRING)

Ravh IT Solutions

Senior Data Enginner

Irvine, CA

$113K - $154K/yr

The ideal candidate will possess strong expertise in Databricks, Apache Spark, Airflow/Astronomer, Data Engineering, DevOps, and Platform Operations , along with proven leadership experience managing ...

New

Astronomer

Sales Engineer

San Francisco, CA · On-site

$200K - $250K/yr

Contribute to the Apache Airflow community by creating technical content and best practices ... Data Engineering Know-How: Familiarity with core data engineering concepts including orchestration ...

INSPYR Solutions

Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

Data Engineer Location: Remote (California) ABOUT THIS FEATURED OPPORTUNITY We are seeking a Junior ... THE OPPORTUNITY FOR YOU Airflow pipeline overhaul * Build out of Athena Operator support for ...

Drunix Solution Inc

Data Engineer

Glendale, CA

$121K - $145K/yr

... Work with Airflow, Spark, Databricks, Delta Lake, and Snowflake • Collaborate with product managers, architects, and engineering teams • Help define best practices, standards, and pipeline ...

TextNow

Data Developer

San Francisco, CA · On-site

They are looking for an experienced Data Developer to design, develop, and maintain their data ... Airflow and Spark. • Have developed scalable, real-time data pipelines using Python/Scala, SQL ...

Redolent, Inc.

Data Engineer

Sunnyvale, CA · On-site

$136K - $163K/yr

Data Engineer ( python, pyspark, scala, airflow) Location:Sunnyvale CA ( Hybrid ) Duration: 6 to 12+ Months Rate: DOE Bachelor or master's degree in computer science, Software Engineering, or a ...

Purple Drive Technologies

Big Data Engineer

Sunnyvale, CA · On-site

$65.50 - $86.50/hr

... and Airflow for data pipeline automation. * Collaborate with cross-functional teams including data scientists, analysts, and DevOps engineers to deliver end-to-end data solutions. * Ensure data ...

SoFi

Senior Manager, Data Engineering

San Francisco, CA · On-site

$124K - $169K/yr

Python fluency for Airflow DAGs, pipeline logic, and data quality scripting • Strong pipeline and ... and mentoring data engineers; strong code review culture • Banking regulatory awareness ...

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Airflow Developer information

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.
What are popular job titles related to Airflow Developer jobs in California? For Airflow Developer jobs in California, the most frequently searched job titles are:
What job categories do people searching Airflow Developer jobs in California look for? The top searched job categories for Airflow Developer jobs in California are:
What cities in California are hiring for Airflow Developer jobs? Cities in California with the most Airflow Developer job openings:
Airflow Developer jobs near you
Infographic showing various Airflow Developer job openings in California as of June 2026, with employment types broken down into 2% Internship, 73% Full Time, 18% Part Time, 2% Temporary, and 5% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution.

Senior Data Enginner

Ravh IT Solutions

Irvine, CA

$113K - $154K/yr

Other

Posted yesterday

Job description

Please find below Requirement 
 
 
 
 
Role: Data Engineering Tower Lead
Location: Irvine, CA
(Enterprise Data Platform & Operations Lead)
Job Description
Position Summary
We are seeking an experienced Data Engineering Tower Lead to lead and manage the enterprise data engineering organization, ensuring the successful delivery, reliability, scalability, and operational excellence of the data platform. This role will be responsible for end-to-end data engineering delivery, platform performance, team leadership, production support, and alignment with business objectives.
The ideal candidate will possess strong expertise in Databricks, Apache Spark, Airflow/Astronomer, Data Engineering, DevOps, and Platform Operations, along with proven leadership experience managing multiple teams and large-scale data programs.
Key Responsibilities
Leadership & Delivery Management
  • Lead and manage the entire Data Engineering Tower across multiple teams, pods, and programs.
  • Own end-to-end delivery of data engineering initiatives, ensuring alignment with business priorities and enterprise goals.
  • Drive program execution, on-time delivery, SLA adherence, and operational excellence.
  • Manage cross-functional dependencies, risks, issues, and escalations.
  • Collaborate closely with business stakeholders, product owners, and technology leadership teams.
Data Engineering & Platform Architecture
  • Oversee the design, development, and optimization of scalable data pipelines and data processing frameworks.
  • Ensure high standards of data quality, governance, scalability, and performance.
  • Establish best practices for enterprise data engineering and platform operations.
  • Lead platform modernization and continuous improvement initiatives.
Databricks & Spark Leadership
  • Provide technical leadership for Databricks platform administration and optimization.
  • Drive advanced Spark development, performance tuning, and workload optimization.
  • Ensure efficient utilization of compute resources and platform scalability.
Workflow Orchestration & Automation
  • Lead enterprise orchestration strategies using Airflow/Astronomer.
  • Design and govern DAG development standards, reliability practices, and workflow optimization.
  • Improve operational efficiency through automation and orchestration frameworks.
DevOps & Infrastructure Automation
  • Implement and oversee DevOps best practices including CI/CD pipelines.
  • Drive Infrastructure-as-Code (IaC) adoption and automation initiatives.
  • Ensure streamlined deployment processes and platform consistency across environments.
Platform Operations & Reliability
  • Establish and maintain highly available, reliable, and scalable data platforms.
  • Define monitoring, alerting, observability, and incident management processes.
  • Lead production support activities and operational readiness programs.
  • Ensure platform stability, disaster recovery preparedness, and business continuity.
Required Qualifications
  • Bachelor''s degree in Computer Science, Information Technology, Engineering, or a related field.
  • 12+ years of experience in Data Engineering, Data Platforms, or Big Data technologies.
  • 5+ years of experience leading large-scale Data Engineering teams and programs.
  • Strong hands-on experience with:
    • Databricks
    • Apache Spark
    • Apache Airflow / Astronomer
    • Enterprise Data Engineering and ETL/ELT frameworks
    • CI/CD pipelines and DevOps practices
    • Infrastructure as Code (Terraform, CloudFormation, etc.)
  • Experience managing enterprise-scale production environments and platform operations.
  • Strong understanding of monitoring, observability, incident management, and reliability engineering.
  • Excellent stakeholder management, communication, and leadership skills.
Preferred Qualifications
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Knowledge of Data Governance, Data Quality, and Data Security frameworks.
  • Experience implementing enterprise-scale Data Lakehouse architectures.
  • Familiarity with SRE (Site Reliability Engineering) practices and platform engineering concepts.
  • Relevant cloud, Databricks, or data engineering certifications are highly desirable.
Key Skills
Databricks | Apache Spark | Airflow | Astronomer | Data Engineering | ETL/ELT | Data Pipelines | DevOps | CI/CD | Infrastructure as Code (IaC) | Platform Engineering | Monitoring & Alerting | Incident Management | Production Support | Cloud Platforms (AWS/Azure/Google Cloud Platform) | Leadership & Stakeholder Management
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