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Airflow Developer Jobs in Minnesota (NOW HIRING)

Stellar IT Group

Data Engineer

Minneapolis, MN · On-site

$119K - $143K/yr

As a Developer, you will build and enhance data pipelines, APIs, and cloud-based services on Google ... Skills Overview: • SQL (5+ years) • Apache Airflow (Cloud Composer) (3+ years) • GCP ...

UnitedHealth Group

Data Engineer

Minnetonka, MN · Remote

$72K - $130K/yr

  • Retirement

Implement CI/CD, infrastructureascode, and DevOps practices for data engineering workloads * Data ... Airflow for workflow orchestration * 2 years of experience in data management principles ...

divvyDOSE

Associate Data | , Minnesota

Minnetonka, MN · On-site

  • Retirement

... engineering, business) to align data solutions with business goals * Build, optimize, and maintain robust data pipelines using Python, SQL, and Apache Airflow * Manage large-scale data ingestion ...

UMR

Associate Data | , Minnesota

Minnetonka, MN · On-site

  • Retirement

... engineering, business) to align data solutions with business goals * Build, optimize, and maintain robust data pipelines using Python, SQL, and Apache Airflow * Manage large-scale data ingestion ...

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Airflow Developer information

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 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.

What are popular job titles related to Airflow Developer jobs in Minnesota?

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

What job categories do people searching Airflow Developer jobs in Minnesota look for?

The top searched job categories for Airflow Developer jobs in Minnesota are:

What cities in Minnesota are hiring for Airflow Developer jobs?

Cities in Minnesota with the most Airflow Developer job openings:

Airflow Developer jobs near you
Infographic showing various Airflow Developer job openings in Minnesota as of August 2026, with employment types broken down into 81% Full Time, and 19% Contract. Highlights an 90% In-person, 4% Hybrid, and 6% Remote job distribution.

AI/ML Engineer

Career Soft Solutions Inc

Minneapolis, MN • On-site

Other

Posted 4 days ago

Job description

Job Title: AI/ML Engineer
Work Location: MinneapolisMN55401Detailed Job Description

The AI/ML Engineer will be responsible for delivering capital-funded cloud migration initiatives involving AI/ML and data platforms.

The resource will work closely with engineering, data, cloud, and business teams to migrate and modernize existing workloads while implementing scalable AI/ML solutions in the Azure ecosystem.

Key responsibilities include:

  • Design, develop, and implement AI/ML solutions for enterprise applications and data platforms.
  • Support the migration of existing AI, analytics, and data workloads to Microsoft Azure and Databricks.
  • Develop scalable data processing and machine learning pipelines using Python, Spark/PySpark, and Airflow.
  • Build and maintain Airflow workflows/DAGs for data and ML pipeline orchestration.
  • Develop, train, evaluate, and optimize machine learning models.
  • Apply strong AI/ML knowledge to solve complex business and technical problems.
  • Collaborate with cloud and data engineering teams to modernize legacy workloads.
  • Ensure migrated workloads meet performance, scalability, security, and reliability requirements.
  • Troubleshoot and optimize cloud-based AI/ML and data processing workloads.
  • Contribute to architecture, technical design, development, testing, deployment, and production support activities.
  • Participate in enterprise-scale cloud migration and modernization programs.
Top 3 Responsibilities
  1. AI/ML Engineering
    Design, develop, optimize, and productionize AI/ML solutions using Python and modern machine learning technologies.
  2. Cloud Migration & Modernization
    Deliver capital-funded initiatives focused on migrating and modernizing AI/data workloads using Azure and Databricks.
  3. Data & ML Pipeline Engineering
    Build and optimize scalable pipelines using Python, Spark/PySpark, and Airflow to support enterprise AI/ML workloads.

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