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Airflow Developer Jobs in Chicago, IL (NOW HIRING)

W. W. Grainger

Senior Software Engineer

Chicago, IL · On-site

$112.90 - $188.10/hr

... Airflow, Node, Next, React, Spectrum address services, Perceptyx, and Kafka. * Work comfortably in CI/CD, Trunk-based branching, and other modern DevOps skillsets. You Have * Bachelor's Degree or ...

Better Trucks

Data Engineering Principal

Chicago, IL · On-site

$150 - $210/hr

Set technical direction for orchestration (Composer/Airflow), including job design, dependency ... Partner with Analytics Engineering and BI to ensure core data models serve reporting and ...

Epsilon

Senior Data Engineer

Chicago, IL · On-site

$109K - $148K/yr

... developer productivity, automation, and platform capabilities by bringing forward modern tools ... Experience with Kafka, Airflow, Docker, Kubernetes, relational and NoSQL databases, and enterprise ...

Publicis Groupe Holdings B.V

Senior Data Engineer

Chicago, IL · On-site

$109K - $148K/yr

... developer productivity, automation, and platform capabilities by bringing forward modern tools ... Experience with Kafka, Airflow, Docker, Kubernetes, relational and NoSQL databases, and enterprise ...

1 point system

Sr. Data Quality Engineer

Chicago, IL · On-site

$118K - $141K/yr

Orchestration (Airflow, Control-M) * APIs & integrations * CI/CD, DevOps * Data modeling & lineage Professional Competencies * Analytical problem-solving with focus on data integrity * High attention ...

The Aspen Group

Manager, Data Engineering

Chicago, IL · On-site

$160K - $190K/yr

Set standards for data modeling, integration, and platform architecture across dbt, Airflow/Cloud ... AI & Engineering Excellence * Lead AI-assisted development (Claude AI/Gemini Enterprise) across ...

Deloitte

Forward Deployed Engineer- AWS

Chicago, IL · On-site

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Bcbsa

Data Engineer (AI/ML)

Chicago, IL · On-site

$118K - $141K/yr

Collaborate with platform and DevOps teams to deploy, scale, and monitor data pipelines using Airflow and Kubernetes. * Participate in code reviews, documentation, and continuous improvement efforts ...

The Aspen Group

Manager, Data Engineering

Chicago, IL

$160K - $190K/yr

Set standards for data modeling, integration, and platform architecture across dbt, Airflow/Cloud ... AI & Engineering Excellence * Lead AI-assisted development (Claude AI/Gemini Enterprise) across ...

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All JobsAirflow Developer JobsAirflow Developer Jobs in Chicago, IL

Airflow Developer information

See Chicago, IL salary details

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$54

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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 Chicago, IL is $54.43, according to ZipRecruiter salary data. Most workers in this role earn between $41.59 and $66.63 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 Chicago, IL?

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

What job categories do people searching Airflow Developer jobs in Chicago, IL look for?

The top searched job categories for Airflow Developer jobs in Chicago, IL are:

What cities near Chicago, IL are hiring for Airflow Developer jobs?

Cities near Chicago, IL with the most Airflow Developer job openings:

Airflow Developer jobs near you
Infographic showing various Airflow Developer job openings in Chicago, IL as of August 2026, with employment types broken down into 82% Full Time, 5% Part Time, and 13% Contract. Highlights an 82% Physical, 6% Hybrid, and 12% Remote job distribution, with an average salary of $113,218 per year, or $54.4 per hour.

Sr. Software Engineer - AI Platforms and Automation

Intelligent Medical Objects, Inc.

Chicago, IL • On-site

$126K - $166K/yr

Other

Posted yesterday

New

Job description

At IMO Health, we combine strengths in software development, artificial intelligence, and clinical expertise to create AI-driven solutions that enhance access to reliable health information, support clinical decision-making, and improve patient outcomes.
We are looking for a Senior Software Engineer to own and evolve the internal software platforms that support IMO Health's terminology and knowledge graph initiatives. This role will maintain and enhance production applications, APIs, integrations, and AI-enabled workflows while helping introduce new AI capabilities into existing business processes as the platform continues to evolve.
The ideal candidate is a software engineer first-someone who enjoys owning and evolving production software while applying AI technologies to solve real business problems. As the platform continues to evolve, you'll help introduce new AI-enabled capabilities into existing business workflows while ensuring the underlying systems remain reliable, scalable, and production-ready.
WHAT YOU'LL DO:
Own and enhance internal platforms
  • Maintain and enhance internally developed applications and tooling that supports terminology management, content creation, mapping, workflow automation, and content delivery.

  • Build and maintain integrations across internal applications, APIs, knowledge bases, databases, and AI services.

  • Contribute to the design and implementation of new automation and AI-enabled capabilities as business needs evolve.

Support reliable production systems
  • Own operational support for AI-enabled applications and workflows in production, including troubleshooting, incident response, release coordination, and ongoing maintenance.

  • Manage application deployments, infrastructure configuration, monitoring, alerting, and operational support for AWS-hosted applications and services.

  • Investigate production issues, perform root-cause analysis, and implement durable solutions that improve reliability.

Enable AI-powered workflows
  • Support AI agents and workflow automation capabilities as they mature from pilot initiatives into scalable production solutions.

  • Develop and troubleshoot cloud-based workflows using AWS services such as Bedrock, Lambda, Glue, S3, IAM, CloudWatch, and MWAA/Airflow.

  • Implement testing, monitoring, and operational readiness practices that improve the quality and reliability of AI-enabled workflows.

Collaborate across teams
  • Partner with clinical, terminology, product, data science, and engineering teams to improve AI-enabled workflows while maintaining appropriate human review and auditability.

  • Mentor team members and promote software engineering best practices for secure, maintainable, and production-ready systems.

WHAT YOU'LL NEED:
  • Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, Machine Learning, or a related technical field; equivalent professional experience will also be considered.

  • 7+ years of professional experience in software engineering, backend engineering, platform engineering, DevOps, MLOps, cloud engineering, or a related discipline, including experience supporting production systems.

  • Strong proficiency in Python and experience building maintainable services, APIs, internal tools, jobs, or workflow automation in production environments.

  • Experience designing, deploying, and supporting cloud-based applications in AWS environments.
  • Experience building or supporting AI-enabled applications using Amazon Bedrock, LLM APIs, knowledge bases, AI agents, retrieval-augmented generation (RAG), or similar technologies.

  • Experience with CI/CD pipelines, Git-based development workflows, automated testing, configuration management, and release practices.

  • Experience with Docker, Kubernetes or other containerized services, Terraform or Infrastructure-as-Code, and production monitoring/alerting tools.

  • Experience with workflow orchestration, data pipelines, or job scheduling tools such as Airflow/MWAA, Glue, Lambda, cron-based jobs, or equivalent technologies.

  • Working knowledge of SQL and relational databases such as PostgreSQL; experience with distributed data or search systems is a plus.

  • Experience building or supporting AI-enabled applications using LLM APIs, retrieval-augmented generation (RAG), knowledge bases, AI agents, or similar technologies.

  • Strong troubleshooting skills, including production issue triage, root-cause analysis, log analysis, and implementation of durable solutions.

  • Ability to partner effectively with domain experts and translate workflow needs into practical, maintainable technical solutions.

  • Strong communication, documentation, and collaboration skills in cross-functional environments.

PREFERRED QUALIFICATIONS:
  • Experience scaling AI-enabled applications or agent-based workflows from prototype or pilot phases into reliable production systems.

  • Experience with modern AI development practices including prompt engineering, tool/function calling, AI evaluation techniques, and AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor.
  • Experience with AI application frameworks such as LangChain, LangGraph, LlamaIndex, or similar technologies.

  • Experience designing or supporting AI evaluation frameworks, quality monitoring practices, or human-in-the-loop workflows for AI-assisted outputs.

  • Experience in healthcare technology, clinical data, clinical terminology, content curation, or other regulated data environments.

  • Familiarity with knowledge graph technologies and semantic standards such as RDF, OWL, SPARQL, SHACL, FHIR, SNOMED CT, LOINC, RxNorm, ICD-10, CPT, or related healthcare standards.

  • Experience working with vector databases, embeddings, search technologies, or other retrieval-based AI architectures.

  • AWS certifications such as AWS Certified Solutions Architect, AWS Certified Machine Learning - Specialty, or AWS Certified Generative AI Developer - Professional.

$140,000 - $200,000 a year
Compensation at IMO Health is determined by job level, role requirements, and each candidate's experience, skills, and location. The listed base pay represents the target for new hires with individual compensation varying accordingly. These figures exclude potential bonuses, equity, or sales incentives, which may also be part of the total compensation package. Our recruiter will provide additional details during the hiring process.
IMO Health also offers a comprehensive benefits package. To learn more, please visit IMO Health's Careers Page.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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