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.
