Global Service Delivery Manager - Data

Description:

The Global Service Delivery Manager Data is accountable for end-to-end transition, stabilization, and run of global data services delivered through GBS.

With 10+ years of experience, the role ensures that data platforms, pipelines, and analytics products are operationally sound, cost-efficient, and scalable, enabling consistent service delivery across regions while supporting Glocal Data Hub operating model.

This role acts as the final accountability layer between build teams, business and Run teams ensuring data services are production-ready and sustainably operated.

Organization chart Indicate schematically the position of the job within the organization. It is sufficient to indicate one hierarchical level above (including possible functional boss) and, if applicable, one below the position. In the horizontal direction, the other jobs reporting to the same superior should be indicated.

Key Responsibilities and Expected Deliverables:

This details what actually needs to be done; the duties and expected outcomes.

Job Description:

Data & Integration Architect (Data Factory)

1. Transition & Production Readiness (Core Accountability)

- Own transition of data platforms and data products from build teams, SIs, and regions into GBS.

- Define and execute structured transition plans covering:

o Knowledge transfer

o Support models (L2/L3)

o Runbooks, SOPs, and operational KPIs

- Lead production readiness and Go-Live / Go-Run sign-off, challenging build teams on supportability.

- Ensure monitoring, alerting, access, and DR procedures are in place before acceptance into BAU.

2. Global Run & Service Operations

- Own BAU operations for global data services across Azure / Databricks platforms.

- Ensure stable operation of data ingestion, integration, transformation, and analytics workloads.

- Lead incident, problem, and change management using ITIL-aligned practices.

- Drive reduction of incident volume, MTTR, and recurring failures through root cause analysis.

3. Service Governance & SLA Management

- Define, track, and report SLAs, OLAs, and KPIs for data services.

- Establish clear service ownership and RACI across GBS, regions, and vendors.

- Provide transparent service reporting to global and regional stakeholders.

- Ensure compliance with data governance, security, and audit requirements.

4. Vendor & AMS Management

- Manage run-mode vendors, AMS partners, and offshore/onshore teams.

- Own vendor performance, commercials, and SLA compliance.

- Drive cost-to-serve optimization without compromising service quality.

- Ensure smooth collaboration between internal GBS teams and external partners.

5. Continuous Improvement & Run Optimization

- Identify opportunities to automate BAU operations, improve monitoring, and reduce manual interventions.

- Standardize run practices across regions and data domains.

- Support platform upgrades, minor enhancements, and patches in run mode.

- Contribute to platform reliability and resilience roadmap.

6. Stakeholder & Regional Engagement

- Act as the single accountable owner for run stability for business and regions.

- Partner closely with Regional Data Hub Heads to manage expectations and priorities.

- Support onboarding of new regions, domains, or data products into GBS.

- Build confidence and trust in data availability and reliability.

Key Outcomes / Success Measures:

- Smooth and predictable transition into BAU

- High platform availability and SLA adherence

- Reduced incidents and operational risk

- Clear ownership, documentation, and audit readiness

- Improved business trust and adoption of data platforms

Education & Experience Indicate the skills, knowledge and experience that the job holder should require to conduct the role effectively

- 10+ years of experience in Data, Analytics, or Platform Service Delivery

- Strong background in GBS / Shared Services / Global delivery models

- Proven experience managing transition & run of enterprise data platforms

- Experience operating multi-region, multi-vendor environments

- Prior exposure to data governance, master data, and enterprise data hubs

- Familiarity with Azure data ecosystem (Data Lake, Databricks, integration services)

- Data pipelines, APIs, and analytics platforms

- Monitoring, alerting, and operational tooling

- ITIL / Service Management

- Cost management and capacity planning for data platforms

- Strong operational rigor and execution mindset

- Ability to challenge build teams on supportability and run readiness

- Mature stakeholder management at senior leadership level

- Calm, structured, and outcome-focused approach

Competencies :

Indicate which of the core competencies and any professional competencies that the role requires

- Rigorous management of results Leadership & People Management

- Employee Engagement Innovation and Change