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• Post :- 28th Nov 2023

We are seeking a talented and experienced individual to join our team as an Airflow Specialist with expertise in migrating jobs from Control-M to Astronomer managed Airflow. In this role, you will play a crucial part in transitioning our workload orchestration from Control-M to Airflow, ensuring seamless and efficient execution of data workflows.

Responsibilities:

Migration Planning:

Collaborate with stakeholders to understand existing Control-M job dependencies, schedules, and requirements.

Develop a comprehensive migration plan outlining the step-by-step process for transitioning jobs to Airflow.

Airflow Implementation:

Configure and set up Astronomer Airflow environments for optimal performance.

Design and implement Airflow DAGs (Directed Acyclic Graphs) to represent and schedule workflows efficiently.

Utilize Airflow operators and sensors to integrate with various systems and technologies.

Job Migration:

Analyze existing Control-M jobs and translate their logic into Airflow workflows.

Ensure data integrity and consistency during the migration process.

Debug and troubleshoot issues that may arise during the migration.

Documentation:

Create comprehensive documentation for migrated workflows, including DAG structures, dependencies, and scheduling details.

Provide training and knowledge transfer sessions to the operations team for managing and maintaining Airflow workflows.

Optimization and Performance Tuning:

Fine-tune Airflow configurations for optimal performance and resource utilization.

Identify and implement improvements to enhance overall system efficiency.

Collaboration:

Work closely with cross-functional teams, including data engineers, developers, and system administrators, to ensure a smooth transition and ongoing support.

Qualifications:

• Proven experience in Astronomer Airflow implementation and management.
• Strong understanding of workflow orchestration and job scheduling concepts.
• Prior experience in migrating jobs from Control-M or similar scheduling tools to Airflow.
• Proficiency in Python scripting for Airflow DAG development.
• Knowledge of database systems, cloud services, and other technologies commonly integrated with Airflow.
• Excellent problem-solving and debugging skills.
• Strong communication skills and the ability to collaborate effectively with diverse teams.

Education and Experience:

• Bachelor’s degree in computer science, Information Technology, or a related field.
• Minimum of 3 years of hands-on experience with Airflow.
• Previous experience with Control-M or similar job scheduling tools is a plus.