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Summary:

The Manager, Global Enterprise Batch Services, is responsible for leading a global operations team that supports enterprise batch processing, workload execution, incident response, alert triage, client delivery monitoring, and operational readiness across distributed, mainframe, and related batch platforms.

This role ensures batch services are executed reliably, issues are identified and escalated quickly, and service-level risks are managed with strong operational discipline. The manager partners closely with application teams, Global Workload Orchestration, engineering, MIM, change management, and business stakeholders to maintain availability, improve resiliency, and reduce operational risk.

As GenAI becomes embedded into daily operations, the manager is also expected to help shift the team from reactive batch monitoring to predictive workload intelligence by using AI-assisted investigation, automated summaries, runbook improvement, workflow automation, and data-driven recommendations to improve service outcomes.

Key Responsibilities:

• Lead Global Enterprise Batch Services operations across shift-based coverage, ensuring batch processing, workload monitoring, escalation, turnover, and service execution are completed accurately, consistently, and on time.

• Provide oversightforbatch job failures, late executions, missed dependencies, SLA exposure, Control-M/ESP issues, file delivery concerns, and related production events that may impact client or business outcomes.

• Ensure timely triage, recovery coordination, ticket updates, communication, handoff, and escalation for incidents, alerts, changes, and operational requests involving GEBS-supported services.

• Partner with Global Workload Orchestration, application owners, engineering, MIM, database, network, vendor, Client Services, Product, Technology, and regional operations teams to resolve issues and maintain follow-the-sun service coverage.

• Manage operational risk across supported services, including settlement batch activity, IPDP and client file deliveries, DPS batch services, Control-M/ESP dependencies, and related application workflows.

• Support incident and change stewardship through clear communications, post-incident recaps, executive summaries, business impact statements, Service Impact Notification inputs, operational readiness reviews, validation criteria, rollback clarity, and batch-service risk assessment.

• Identify recurring failures, false positives, alert noise, manual intervention points, and operational patterns that can be improved through automation, monitoring enhancements, process redesign, dashboards, knowledge-basemodernization, or client self-service capabilities.

• Promote responsible GenAI adoption by helping the team use approved AI tools for incident summarization, knowledge retrieval, runbook validation, operational analysis, documentation generation, SLA-risk forecasting, alert correlation, restart recommendations, and repetitive workflow automation.

• Maintain appropriate human oversight for high-risk decisions, client-impact assessments, production changes, critical incidents, and any AI-generated recommendation before execution.

• Develop and mentor team members in batch operations, incident management, Control-M/ESP fundamentals, automation thinking, GenAI fluency, operational documentation, service ownership, and cross-regional collaboration.

• Provide Director delegate support when required, including management communication, operational representation, escalation support, and leadership coverage during major events or business-critical changes.

Leadership Expectations & Success Measures:

• Maintainreliable batch operations with strong focus on SLA protection, timely escalation, accurate turnover, and minimal client or business impact.

• Demonstrate effective leadership of a global shift-based team, including prioritization, coaching, issue ownership, and cross-regional coordination.

• Ensure incidents, changes, alerts, and operational requests are handled in accordance with documented procedures, ITIL practices, and change/incident stewardship expectations.

• Improve operational effectiveness by reducing recurring incidents, unnecessary alerts, manual rework, and avoidable escalations through process improvement and automation.

• Expand responsible GenAI usage across the team, with measurable adoption in incident summaries, knowledge retrieval, runbook updates, operational analysis, and repetitive workflow reduction.

• Build predictive batch operations capability by using data, trend analysis, and AI-assisted insights to identify SLA risk, failure patterns, workload constraints, and service improvement opportunities.

• Communicate clearly with technical teams, business partners, and leadership, especially during incidents, high-risk changes, and service-impacting events.