MetLife

MGCC GG 13– Data Governance EDAG Director

Position Title:

MGCC GG 13– Data Governance EDAG Director

Function, Responsibility Level: 

Reports to (Responsibility Level): GG 13 or above 

Supervises: 

GG 12.1 

GG 12.2 

GG 11.2

GG11.1

Location:

Global Grade: 13

Cost Center (85 series): 

Complexity: OSTG

PID/s Load Mapping:

Position Summary

 MetLife established a Global capability center (MGCC) in India to scale and mature Data & Analytics, technology and operations capabilities in a cost-effective manner and make MetLife future ready. The center is integral to Global Technology and Operations with a focus to protect & build MetLife IP, promote reusability and drive experimentation and innovation. The Data & Analytics team in India mirrors the Global D&A team with an objective to drive business value through trusted data, scaled capabilities, and actionable insights. The operating models consists of business aligned data officers- US, Japan and LatAm & Corporate functions enabled by enterprise COEs- data engineering, data governance and data science

Role Value Proposition:  

As the MetLife Global Capability Center(MGCC)'s on-site leader for the Enterprise Data and AI Governance (EDAG) organization, this role is accountable for building and leading high-performing teams, driving talent acquisition, talent development & engagement, culture building, local execution in alignment with EDAG's objectives and priorities

Job Responsibilities

• Own end-to-end talent sourcing and hiring for the India-based workforce, including identifying needs, partnering with recruiting, interviewing candidates, and ensuring timely filling of open roles across employees and consultants.
• Serve as the on-site leader and primary point of contact for the India-based workforce, ensuring the team is fully staffed, operationally strong, and closely aligned to enterprise priorities, values, and ways of working.
• Act as a culture carrier who sets the tone for inclusive, collaborative behaviors and a high-performance mindset, while attracting and selecting talent that strengthens the team culture.
• Provide day-to-day people leadership, guidance, and support to team members, including workload planning, removing obstacles, managing PTO coverage and communication, and escalating issues as needed to ensure continuity of service.
• Partner closely with onshore leadership to forecast talent needs, align on skill requirements, and maintain clear visibility into hiring plans, staffing levels, and team performance across locations.
• Lead onboarding and assimilation for new hires, ensuring smooth ramp-up, engagement, and productivity through intentional onboarding plans and ongoing connection to the broader organization.
• Drive talent development by proactively identifying high-potential employees, investing in skill growth, and building and maintaining a strong, diverse succession pipeline to reduce dependency on single points of failure.
• Ensure cross-training and back-up coverage for critical processes, using staffing and skill planning as a risk mitigation strategy to maintain operational resilience

Knowledge, Skills and Abilities

Education

Bachelor’s degree in computer science, information technology or equivalent educational qualification

Technical Skills and Experience

• 16+ years of relevant experience across a combination of data governance, data quality, and/or AI governance capabilities—including business metadata, data quality controls and exception management, AI risk and ethics, data modeling, and related governance tools

• Working knowledge across a combination of data governance, data quality, and/or AI governance capabilities—including business metadata, data quality controls and exception management, AI risk and ethics, data modeling, and related governance tools. 
• Understanding of the Data & Analytics lifecycle and Agile delivery models.
• Agile methodologies (Scrum, SAFe)
• Experience operating in large, matrixed enterprise environments.
• Analytical, structured problem‑solving, written & verbal communication, and presentation skills.
• Storytelling, partner, and senior stakeholder engagement experience

Good to Have (Preferred)

• Exposure to Gen AI, AI governance, or Responsible AI frameworks.
• Agile tools such as Azure DevOps. 
• Banking, Financial Services, and Insurance domain experience.
• Familiarity with DCAM or similar data management maturity frameworks.
• Experience working with global or federated data governance models.