AWS Airflow - Control-M Resource
Pi Square Technologies LLC
University of South Florida, Tampa, FL 33620, USA
6/5/2026
Full time
AWS Airflow - Control-M Resource
Role Overview
Senior-level Workload Automation Engineer to support the operationalization of AWS Airflow (MWAA) within an enterprise environment leveraging BMC Control M as the primary scheduling and SLA management platform.
This role will focus on defining and implementing integration strategies, aligning Airflow with existing enterprise standards, and establishing consistent monitoring, alerting, and operational procedures across a hybrid workload automation ecosystem.
Key Responsibilities
• Define and implement the integration strategy between AWS Airflow (MWAA) and Control M, ensuring alignment with enterprise scheduling architecture and long-term roadmap
• Establish and standardize monitoring, alerting, and operational support models for Airflow, consistent with existing Control M practices and SLA requirements
• Integrate Airflow workflows into enterprise workload automation standards, procedures, and governance frameworks, including incident management and escalation processes
• Enable centralized visibility and monitoring across Airflow and Control M, ensuring consistent operational oversight and reporting
• Design and support hybrid orchestration patterns, coordinating workload execution across cloud-native (Airflow) and enterprise scheduling (Control M) platforms
• Develop runbooks, operational procedures, and support documentation to ensure sustainable and scalable support models
• Collaborate with IT Operations and Platform teams to define ownership boundaries and streamline operational workflows
• Identify opportunities to reduce manual effort, improve reliability, and enhance SLA performance across workload automation platforms
Role Overview
Senior-level Workload Automation Engineer to support the operationalization of AWS Airflow (MWAA) within an enterprise environment leveraging BMC Control M as the primary scheduling and SLA management platform.
This role will focus on defining and implementing integration strategies, aligning Airflow with existing enterprise standards, and establishing consistent monitoring, alerting, and operational procedures across a hybrid workload automation ecosystem.
Key Responsibilities
• Define and implement the integration strategy between AWS Airflow (MWAA) and Control M, ensuring alignment with enterprise scheduling architecture and long-term roadmap
• Establish and standardize monitoring, alerting, and operational support models for Airflow, consistent with existing Control M practices and SLA requirements
• Integrate Airflow workflows into enterprise workload automation standards, procedures, and governance frameworks, including incident management and escalation processes
• Enable centralized visibility and monitoring across Airflow and Control M, ensuring consistent operational oversight and reporting
• Design and support hybrid orchestration patterns, coordinating workload execution across cloud-native (Airflow) and enterprise scheduling (Control M) platforms
• Develop runbooks, operational procedures, and support documentation to ensure sustainable and scalable support models
• Collaborate with IT Operations and Platform teams to define ownership boundaries and streamline operational workflows
• Identify opportunities to reduce manual effort, improve reliability, and enhance SLA performance across workload automation platforms