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Airflow Developer Jobs in Novato, CA (NOW HIRING)

Senior Data Engineer ID71671

San Francisco, CA · On-site +1

$124K - $169K/yr

You will orchestrate workflows using Airflow, Prefect, or Dagster, implement data quality and ... or similar). - DevOps / DataOps Practices : Strong skills in version control (Git ...

Senior Data Engineer ID71671

San Francisco, CA · On-site

$124K - $169K/yr

You will orchestrate workflows using Airflow, Prefect, or Dagster, implement data quality and ... or similar). - DevOps / DataOps Practices : Strong skills in version control (Git ...

New

Data Engineer

San Francisco, CA · On-site

$134K - $162K/yr

The Data Engineer will lead the design and implementation of scalable data workflows, architect ... Airflow, dbt, Spark, or equivalent). • Design data models and storage systems optimized for ...

Senior Data Engineer ID75059

San Francisco, CA · On-site

$124K - $169K/yr

You will implement Python-based ETL/ELT pipelines, orchestrate workflows with Airflow, develop ... The role combines hands-on engineering with technical consulting responsibilities, translating ...

Senior Data Engineer ID75059

San Francisco, CA · On-site +1

$124K - $169K/yr

You will implement Python-based ETL/ELT pipelines, orchestrate workflows with Airflow, develop ... The role combines hands-on engineering with technical consulting responsibilities, translating ...

Senior Data Engineer ID75059

San Francisco, CA · On-site

$124K - $169K/yr

You will implement Python-based ETL/ELT pipelines, orchestrate workflows with Airflow, develop ... The role combines hands-on engineering with technical consulting responsibilities, translating ...

About the Role We're looking for a Machine Learning Engineer to design, build, and deploy ... Are familiar with ML infrastructure tools such as MLflow, Weights & Biases, Airflow, Kubeflow, or ...

Showing results 21-40

Airflow Developer information

See Novato, CA salary details

$20

$62

$95

How much do airflow developer jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for airflow developer in Novato, CA is $62.04, according to ZipRecruiter salary data. Most workers in this role earn between $47.40 and $75.91 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.

What are popular job titles related to Airflow Developer jobs in Novato, CA?

For Airflow Developer jobs in Novato, CA, the most frequently searched job titles are:

What cities near Novato, CA are hiring for Airflow Developer jobs?

Cities near Novato, CA with the most Airflow Developer job openings:

Infographic showing various Airflow Developer job openings in Novato, CA as of August 2026, with employment types broken down into 77% Full Time, 10% Part Time, and 13% Contract. Highlights an 79% Physical, 6% Hybrid, and 15% Remote job distribution, with an average salary of $129,035 per year, or $62 per hour.

Senior Data Engineer ID71671

AgileEngine

San Francisco, CA • On-site, Remote

$124K - $169K/yr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you\'re looking for a place to grow, make an impact, and work with people who care, we\'d love to meet you!
ABOUT THE ROLE
We are looking for a Senior Data Engineer to architect, build, and scale a modern data platform — designing production-grade ETL/ELT pipelines, optimizing Snowflake data warehouse schemas, and establishing robust DataOps practices. You will orchestrate workflows using Airflow, Prefect, or Dagster, implement data quality and lineage frameworks, integrate third-party REST APIs and event-driven sources, and apply software engineering standards including CI/CD, Docker, and automated testing to data repositories. The role prioritizes clean, well-tested Python code and a deep commitment to data reliability and accessibility.
WHAT YOU WILL DO
- Data Pipeline Development: Design, build, and maintain reliable, scalable ETL/ELT workflows that process batch and streaming data from diverse sources.
- Data Warehousing & Modeling: Design efficient, production-ready schemas (normalized and denormalized) in Snowflake to optimize query performance and enable enterprise analytics.
- API & Event Integration: Connect and ingest data from third-party REST APIs, event-driven streams, and batch sources into core data storage platforms.
- Orchestration: Maintain and expand workflow orchestration pipelines using modern tools (Airflow, Prefect, or Dagster).
- Data Quality & Observability: Implement automated testing, validation, lineage tracking, and proactive alerting frameworks to guarantee data accuracy and system uptime.
- DataOps & Engineering Standards: Drive CI/CD best practices, maintain code bases using Git and Docker, and adopt basic Infrastructure-as-Code (IaC) patterns.
- Code Excellence: Apply modern software engineering standards—including design patterns, automated unit/integration testing, and clear documentation—to data repositories.
MUST HAVES
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- 4+ years of experience as a Data Engineer.
- Core Python Fundamentals: Demonstrable expertise writing modular, maintainable, and well-tested Python code (OOP/functional patterns, package management, standard testing frameworks).
- Advanced SQL & Modeling: Deep knowledge of complex SQL queries, query optimization, database design principles, and normalization/denormalization patterns.
- Data Warehousing: Solid, hands-on experience building, managing, and optimizing data architectures within Snowflake.
- Workflow Orchestration: Production experience using workflow orchestration engines like Apache Airflow, Prefect, or Dagster.
- Integrations & Ingestion: Hands-on experience working with REST APIs, event-driven architectures, and both batch and streaming pipelines.
- Data Quality & Lineage: Experience building automated data quality checks, data lineage, and alerting mechanisms (e.g., using tools like dbt test, Great Expectations, or similar).
- DevOps / DataOps Practices: Strong skills in version control (Git), containerization (Docker), CI/CD automation, and familiarity with Infrastructure-as-Code basics.
- Upper-intermediate English level.
NICE TO HAVES
- Experience with dbt (data build tool) for data transformations.
- Familiarity with major cloud providers (AWS, GCP, or Azure).
- Exposure to message streaming tech like Apache Kafka or AWS Kinesis.
PERKS AND BENEFITS
- Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
- Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
- Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
- Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
- Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
- Well-being & support: access local well-being programs and people-focused support tailored to your location