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Airflow Developer Jobs in Indiana (NOW HIRING)

Senior AI/ML Engineer

Indianapolis, IN

$99K - $137K/yr

Overview: AI/ML Engineer: 10+ Years of Experience Skills AI/ML Strong Python Coding Experience LLM workflows (AWS/GCP/Azure) ETL workflows using Spark, Glue, Airflow, • Design, develop, and ...

... Airflow) + Experience creating CI/CD pipelines (prefer using GitLab) + Packaging and deploying ... Education/Experience: 8+ years of experience as a developer, preferably in an Insurance or ...

... Engineer - Senior Associate, you will focus on designing and building data infrastructure and ... Airflow and Apache Hadoop for scalable data processing and workflow management - Building and ...

Data Engineer

South Bend, IN

$112K - $134K/yr

Experience with orchestration tools (Airflow, Azure Data Factory, etc.) * Knowledge of real-time/streaming data processing * Familiarity with DevOps practices (CI/CD, version control) * Experience ...

Data Engineer

South Bend, IN · On-site

$112K - $134K/yr

Experience with orchestration tools (Airflow, Azure Data Factory, etc.) * Knowledge of real-time/streaming data processing * Familiarity with DevOps practices (CI/CD, version control) * Experience ...

Data Engineer

South Bend, IN · On-site

$112K - $134K/yr

Experience with orchestration tools (Airflow, Azure Data Factory, etc.) * Knowledge of real-time/streaming data processing * Familiarity with DevOps practices (CI/CD, version control) * Experience ...

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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 job categories do people searching Airflow Developer jobs in Indiana look for? The top searched job categories for Airflow Developer jobs in Indiana are:

Senior AI/ML Engineer

Purple Drive

Indianapolis, IN

$99K - $137K/yr

Other

Posted 5 days ago


Job description

Overview:
AI/ML Engineer: 10+ Years of Experience
Skills
AI/ML
Strong Python Coding Experience
LLM workflows
(AWS/GCP/Azure)
ETL workflows using Spark, Glue, Airflow,
• Design, develop, and maintain scalable Python applications, libraries, and scripts for data pipelines, APIs, and LLM workflows, ensuring code quality and reusability.
• Craft, test, and optimize prompts for generative AI/LLM models; integrate Hugging Face transformers and fine-tuned models into ETL and downstream applications.
• Build and manage robust ETL workflows using Spark, Glue, Airflow, or similar; handle structured/unstructured data ingestion, transformation, and persistence across data lakes, warehouses, and RDS systems.
• Develop and operationalize LLM/transformer models via Hugging Face ecosystem; optimize inference pipelines for latency, scalability, and cost efficiency across cloud (AWS/GCP/Azure) and containerized environments (ECS/Fargate/Kubernetes).