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Airflow Developer Jobs in Georgia (NOW HIRING)

DataStage Developer Location: Atlanta, GA / Nashville, TN Duration: Long term contract Note ... Familiarity with orchestration tools like Apache Airflow * Python or scripting experience

Software Developer - Adobe MarTech Location: Duluth, GA - Hybrid, 2 days onsite weekly Duration: 6 ... BigQuery/Airflow pipelines, optimize MongoDB/PostgreSQL for <500ms latency, and support CI/CD ...

Data Engineer

Atlanta, GA · On-site

$60 - $68/hr

Top Skills' Details 1- Databricks data modeling w/ Python 2- Azure ETL / Data analysis 3- Spark/Hive/Airflow 5-10 Years Focused on manipulating data in a software engineering capacity. Some of that ...

Data Engineer III

Atlanta, GA · On-site

$110K - $132K/yr

Proficiency in Databricks, Azure, Spark, Hive, and Airflow is required. Key Responsibilities Data Engineering & Pipeline Development * Design, build, and maintain scalable and reliable data pipelines

Position: ETL/SSIS Developer Location: Atlanta, GA / Nashville, TN Duration: Long term contract ... Familiarity with orchestration tools like Apache Airflow * Python or scripting experience

Data Engineer IV

Atlanta, GA · On-site

$110K - $132K/yr

Manage data orchestration workflows (e.g., Airflow or equivalent) * Implement CI/CD and Git-based workflows for data pipelines AI-Assisted & Modern Engineering Practices * Leverage AI tools or ...

Data Engineer 4

Atlanta, GA · On-site

$110K - $132K/yr

... g., Airflow or equivalent) • Experience with CI/CD and Git based workflows for data pipelines • Experience using AI tools or copilots to assist with data engineering tasks (SQL development ...

Support workflow orchestration platforms (e.g., Airflow) to ensure successful job execution and ... Collaborate with Engineering, Product, and Data teams to resolve issues and enhance system ...

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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.

Python Data Engineer (Airflow, Kafka, Spark) - Q125

R2 Technologies Corporation

Alpharetta, GA • On-site

$111K - $134K/yr

Full-time

Medical, Retirement, PTO

Re-posted yesterday


Job description

Overview:
R2 Technologies Corporation (R2), headquartered in Alpharetta, GA, is a leading IT services provider specializing in Java, .NET, Big Data, Cloud Computing (AWS, GCP, Azure), Artificial Intelligence (AI), Machine Learning (ML), software development, project management, SAP, and enterprise resource planning (ERP). We empower clients-from startups to Fortune 1000 companies-with scalable, platform-based solutions and data-driven insights using modern cloud technologies. Our commitment to blending highly skilled talent with innovative productivity platforms ensures rapid delivery of business value, making us one of the most respected and trusted technology companies in the United States. At R2, we're passionate about driving operational excellence and competitive advantage for our clients through cutting-edge AI, ML, and cloud solutions. Join our team and help shape the future of technology innovation!
Python Data Engineer (Airflow, Kafka, Spark)
Location: Alpharetta, GA (willing to travel to client locations)
Employment Type: Full-Time (W2)
Role Overview
We are seeking a proficient Python Data Engineer to build and manage data pipelines using Airflow, Kafka, and Spark. This role focuses on developing scalable ETL/ELT workflows for streaming and batch data processing.
Key Responsibilities
  • Design and implement data pipelines using Python with Airflow for orchestration and scheduling.
  • Integrate Kafka for streaming data and Spark for processing large-scale datasets.
  • Develop ETL/ELT workflows to transform and load data into storage or analytics systems.
  • Optimize pipelines for performance, reliability, and scalability in distributed environments.
  • Collaborate with data teams to ensure data quality and availability for downstream applications.
  • Monitor and troubleshoot data workflows to maintain seamless operations.

Required Qualifications
  • Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent experience).
  • 3 years of experience as a Data Engineer with Python, focusing on Airflow, Kafka, and Spark.
  • Proficiency in building ETL/ELT pipelines for streaming and batch data processing.
  • Experience with Kafka for real-time data streaming and Spark for distributed data processing.
  • Strong understanding of data engineering principles and pipeline automation.

Preferred Qualifications
  • Familiarity with alternative orchestration tools like Luigi for data workflow management.
  • Exposure to cloud platforms like AWS or GCP for hosting data pipelines.
  • Knowledge of monitoring tools like Grafana for pipeline observability.

Compensation & Benefits
  • Competitive salary and comprehensive benefits package (healthcare, PTO, 401k).
  • Opportunities for professional growth and upskilling in AI and cloud technologies.

R2 Technologies Corporation is an equal opportunity employer and values diversity in the workplace.
Skills:
Python, Airflow, Kafka, Spark, Data Engineer, ETL, ELT, Streaming