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Airflow Developer Jobs in Illinois (NOW HIRING)

ClifyX

ReactJS with Azure developer

Chicago, IL · On-site

$56.75 - $70.25/hr

... Apache Airflow on Kubernetes (AKS) using Helm. • Writing DAGs in Python for ETL and data ... DevOps & Containerization • Docker -- multi-stage builds for React and Python/Node apps. • Helm ...

Collabera

GIS - Analyst

Mossville, IL

Installing tools and job scheduling or data workflow tools like Crontab or Apache Airflow * Programming experience with one or more programming languages * Python, object oriented programming ...

CYNET SYSTEMS

Full Stack Developer

Chicago, IL · On-site

$60 - $65/hr

Working knowledge of Apache Airflow for workflow orchestration. Experience with Apache Spark for ... Experience working with AI-assisted engineering tools (e.g., GitHub Copilot, ChatGPT, Cursor ...

CYNET SYSTEMS

Full Stack Developer

Chicago, IL · On-site

$60 - $65/hr

Working knowledge of Apache Airflow for workflow orchestration. * Experience with Apache Spark for ... Experience working with AI-assisted engineering tools (e.g., GitHub Copilot, ChatGPT, Cursor ...

Apex Informatics

Data engineer

Chicago, IL · On-site

$118K - $141K/yr

Looking for 2 to 4 years of professional experience as a Data engineer Chicago, IL. Skills required ... SAAS, SQL, Snowflake and Airflow. * Strong SQL Skills: Proficiency in writing complex queries ...

Point72

Quantitative Developer

Chicago, IL

Quantitative Developer for a PM team focused on systematic credit and related asset classes. This ... Knowledge of SQL, JavaScript, Apache airflow. * Strong communication skills. * Willingness to take ...

Point72

Quantitative Developer

Chicago, IL · On-site

Quantitative Developer for a PM team focused on systematic credit and related asset classes. This ... Knowledge of SQL, JavaScript, Apache airflow. * Strong communication skills. * Willingness to take ...

Omnicom

Senior Data Engineer

Chicago, IL · On-site

$109K - $148K/yr

The ideal candidate is highly skilled in Python, Apache Airflow, AWS Lambda, DynamoDB, and dbt, and ... Git, and DevOps practices. - Strong problem-solving and communication skills. Preferred ...

Omnicom

Senior Data Engineer

Chicago, IL

$109K - $148K/yr

The ideal candidate is highly skilled in Python, Apache Airflow, AWS Lambda, DynamoDB, and dbt, and ... Git, and DevOps practices. - Strong problem-solving and communication skills. Preferred ...

AgileEngine

Senior Data Engineer ID71671

Chicago, IL · On-site

$109K - $148K/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 ...

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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 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 Illinois?

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

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

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

What cities in Illinois are hiring for Airflow Developer jobs?

Cities in Illinois with the most Airflow Developer job openings:

Airflow Developer jobs near you
Infographic showing various Airflow Developer job openings in Illinois as of August 2026, with employment types broken down into 85% Full Time, 2% Part Time, and 13% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution.

Senior Workflow Orchestration Engineer (Airflow & Scheduling Platforms)

Benton Partners

Chicago, IL • On-site

$140 - $210/hr

Other

Posted 2 days ago

New

Job description

Senior Workflow Orchestration Engineer (Airflow & Scheduling Platforms)
  • NY or Chi, NYC
About therole

We'reseeking a seasoned engineer to design,operate, and scale our workflow orchestration platform with a primary focus on Apache Airflow.You'llown the Airflow control plane and developer experience end-to-end-architecture, automation, security, observability, and reliability-while also evaluating andoperatingcomplementary schedulers whereappropriate.You'llbuild automation infrastructure and partner across data, trading, and engineering teams to deliver mission-critical pipelines at scale.

Whatyou'lldo
  • Architect, deploy, andoperateproduction-grade Airflow on Kubernetes including all components and user application dependencies, with focus on upgrades, capacity planning, HA, security, and performance tuning
  • Operate a multi-scheduler ecosystem:determinewhen to use Airflow, distributed compute schedulers, or lightweight task runners based on workload requirements; provide unified developer experience across schedulers
  • Build automation infrastructure: Terraform modules and Helm charts withGitOps-driven CI/CD for environment provisioning, upgrades, and zero-downtime rollouts
  • Standardize the developer experience: DAG repo templates, shared operator libraries, connection and secrets management, dependency packaging, code ownership, linting, unit testing, and pre-commit hooks
  • Implement comprehensive observability: metrics collection, dashboards, distributed tracing, SLA/latency monitoring, intelligent alerting, and runbook automation
  • Enable resilient workflow patterns: build idempotency frameworks, retry/backoff strategies, deferrable operators and sensors, dynamic task mapping, and data-aware scheduling
  • Ensure reliability at enterprise scale: architect and tune resource allocation (pools, queues, concurrency limits) to support high-throughput workloads-optimizelarge-scale backfill strategies; develop comprehensive runbooks and lead incident response/postmortems
  • Partner with teams across the organization to provide enablement, documentation, and self-service tooling
  • Mentor engineers, contribute to platform roadmap and technical standards, and drive engineering best practices
Required qualifications
  • 5-8+ years building/operating data or platform systems; 3+ years running Airflow in production at scale (hundreds-thousands DAGs and high task throughput).
  • Deep Airflowexpertise: DAG design and testing, idempotency, deferrable operators/sensors, dynamic task mapping, task groups, datasets, pools/queues, SLAs, retries/backfills, cross-DAG dependencies.
  • Strong Kubernetes experience running Airflow and supporting services: Helm, autoscaling, node/pod tuning, topology spread, network policies, PDBs, and blue/green or canary strategies.
  • Automation-first mindset: Terraform, Helm,GitOps(Argo CD/Flux), and CI/CD for platform lifecycle; policy-as-code (OPA/Gatekeeper/Conftest) for DAG, connection, andsecretschanges.
  • Proficiencyin Python for authoring operators/hooks/utilities; solid Bash; familiarity with Go or Java is a plus.
  • Observability and SRE practices: Prometheus/Grafana/StatsD, centralized logging, alert design, capacity/throughput modeling, performance tuning.
  • Data platform experience with at least one major cloud (AWS/Azure/GCP) and systems like Snowflake/BigQuery/Redshift, Databricks/Spark, EMR/Dataproc; strong grasp of IAM, VPC networking, and storage (S3/GCS/ADLS).
  • Security/compliance: SSO/OIDC, RBAC,secretsmanagement (Vault/Secrets Manager), auditing, least-privilege connection management, and change control.
  • Proven incident leadership, runbook creation, and platform roadmap execution; excellent cross-functional communication.
Nice to have
  • Experience operating alternative orchestrators (Prefect 2.x,Dagster, Argo Workflows, AWS Step Functions) and leading migrations to/from Airflow.
  • OpenLineage/Marquez adoption; Great Expectations or other data quality frameworks; data contracts.
  • Cost optimization and capacity planning for schedulers and workers; spot instance strategies.
  • Multi-region HA/DR for Airflow metadata DB; backup/restore and disaster drills.
  • Building internal developer platforms/portals (e.g., Backstage) for self-service pipelines.
  • Contributions to Apache Airflow or provider packages; familiarity with recent AIPs/Airflow 2.7+ features.
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