Administrator - BMC Control M, Python
Confirmed on the employer's own hiring board on Oct 2, 2026. First seen by Alion on Sep 30, 2026.
Job Summary
Responsible for the administration, design, scheduling, automation, and support of BMC Control-M workload automation platforms. This role manages enterprise batch processing, job scheduling, agent and plugin administration, SLA monitoring, performance optimization, troubleshooting, security compliance, disaster recovery, and DevOps integration across distributed, cloud, and mainframe environments.
Key Responsibilities
: Key Responsibilities Design, build, and maintain end-to-end batch workflows and job schedules using Control-M. Administer Control-M components including Enterprise Manager (EM), Servers, Agents, and Application Integrator plugins. Configure job dependencies, calendars, resources, SLAs, critical paths, alerts, and workload policies. Support agent deployment, high availability configurations, secure communications, and plugin integrations. Monitor batch operations, forecast workload performance, and ensure SLA adherence. Lead incident resolution, root cause analysis (RCA), problem management, and operational improvements. Manage user access, security controls, credential vaulting, audit compliance, and change management processes. Perform platform upgrades, patching, performance tuning, housekeeping, and capacity planning. Enable automation through Control-M Automation API, CI/CD integration, and Infrastructure-as-Code practices. Support file transfer orchestration, data pipeline scheduling, backup/recovery processes, and disaster recovery testing. Partner with application, infrastructure, and business teams to onboard workloads, manage dependencies, and communicate batch health and operational status.
Skill Requirements
Required Skills Strong experience with BMC Control-M Administration and Enterprise Workload Automation. Expertise in job scheduling, batch operations, SLA management, and workload orchestration. Experience with Linux/Unix, Windows, and preferably Mainframe environments. Knowledge of Control-M Automation API, REST APIs, JSON, and CI/CD tools. Strong troubleshooting, performance tuning, and root cause analysis skills. Understanding of security, compliance, high availability, and disaster recovery concepts.
Other Requirements
Cloud integrations (AWS, Azure, GCP) and Kubernetes scheduling. Experience with MFT, ETL/Data Platform orchestration, and data pipeline automation. Monitoring and observability tools such as Splunk, Grafana, and AppDynamics. Scripting and automation using Shell, PowerShell, or Python.