| GG13 Director -Data Management |
| Position Title: GG13 Director – Data Management | Reports to (Responsibility Level):GG15 VP –Analytics | Supervises: Data Architects, data engineers, Platform engineers (Dev ops and BI platforms) and scrum leads |
| Location: Noida | Global Grade: GG13 | Complexity: OSTG | PID/s Load Mapping: |
| Position Summary |
| MetLife established a Global capability center (MGCC) in India to scale and mature Data & Analytics, technology capabilities in a cost-effective manner and make MetLife future ready. The center is integral to Global Technology and Operations with a 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 engineering(EDE) 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 EDE's objectives and priorities This role is integral to Enterprise Data Engineering organization. This role will directly report into MGCC D&A leader and dots into Enterprise Data Engineering leader. |
| Job Responsibilities |
| - Leadership: a key member of the MGCC D&A leadership & Enterprise Data engineering teams- contribute to shaping up the strategic imperatives and driving commercial value using data and analytics. Build strategic partnerships with various Operations, Risk, Technology leaders at Enterprise and MGCC levels to ensure alignment and collaboration across all functions
- Co-develop and execute the Enterprise data engineering roadmap aligned with business objectives and Global D&A strategy
- In collaboration with Data offices, Enterprise teams within Global D&A, Technology, Architecture Review Boards, translating business & technical challenges into enterprise-grade data accelerators and scalable designs
- Assess current state technology and data infrastructure (on-prem, cloud, legacy technologies, technology currency), evolving information needs, performance considerations and recommend future state solution & data architecture
- Architect, design and direct the development and delivery of efficient, scalable, and trustworthy data accelerators and frameworks
- Review design options and direct team to choose the right design for data engineering & building right data pipes:Extract, Transform and Load (ETL) or Extract, Load and transform (ELT)
- Review current state data architecture, data stores- warehouses, hubs, lakes etal and recommended opportunities for efficient data storage, processing and retrieval
- 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.
- Align team in MGCC (across locations) to Global D&A, Enterprise Data Engineering organization and integrate talent from development and engagement standpoint
- Team Development & Cultural Transformation: Enable cultural shift from a traditional operations & technology-focused data team to a business-outcome-driven mindset, develop training programs to enhance domain, data knowledge. Acquire, engage and develop contemporary and ‘fit for purpose’ talent
- Proactive D&A leadership: Proactively identify and propose data-driven solutions to business challenges, leading data and analytics organization beyond traditional service provider role to become strategic innovation partner driving business transformation
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Education, Technical Skills & Other Critical Requirement | |
Education | Bachelor’s/ Master’s degree in an information technology/computer science or relevant domain | |
Experience (In Years) | - 16+years of solutions development experience, including 12+ years in data products & solutions delivery.
- 12+ years of insurance industry experience, or other consumer financial services experience with similar complexity
- 5+ years of people leadership, talent development and engagement
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Technical Skills | - Azure, Hadoop/Databricks, Hive, SQL
- Solution architecture, data architecture, data analysis & data engineering skills. Solutioning skills to build trustworthy and efficient data layers for a variety of consumption needs such as reporting, advanced analytics, data APIs, AI et al
- Expertise at data architecture principles: centralized and decentralized approaches & applicability
- Data governance- data classification, data lineage, data profiling, data quality, data transformation data validation, data ops.
- Expertise at building, maintaining range of data stores - Data warehouses, data marts, data lakes, data mesh etc.
- Expertise working with large and complex internal, external, structured, and unstructured datasets
- Responsible development of Data solutions
- Demonstrated success in leading data and analytics teams and delivering business value through creative data solutions, while effectively interacting with multiple stakeholders in a complex organization
- Agile methodologies & tools.
- Understanding of legacy insurance platforms and modernization initiatives
- Excellent in stakeholder management and executive communication. Strong conceptual and creative problem-solving skills; empathy led engagement with focus on stakeholder motivation, needs and aspirations.
- Knowledge of HIPAA and other relevant consumer data regulations, emerging Cloud, Data trends
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Other Critical Requirements | Preferred: Appreciation for data science, machine learning techniques and their business applications within banking and financial services & insurance industries; familiarity with new age AI techniques such as Generative AI (GenAI), large language models (LLMs) and their business applications | |
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