Senior Data Analyst I

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

Data Analyst plays a critical role in data and analytics life cycle and significantly contributes to production grade data and analytics solutions. The role requires one to demonstrate analytical, SQL, Big Data and Cloud expertise. This role mentors Data Analysts. It is an individual contributor role, expected to solve wide ranging business problems

Job Responsibilities

• Understand business requirements to author functional requirements documents to develop and deliver production grade data and analytics solutions.
• Analyze data in the context of business processes, business and functional requirements
• Provide relevant inputs to data architecture, engineering, governance, modeling, quality and data science teams
• Validate the data loaded by engineering team
• Collaborate with multiple partners from Business, Technology, Operations and D&A capabilities (Data Governance, Data Quality, Data Modeling, Data Architecture, Data science, BI & insights)

Mentor Data Analysts

Independently lead design, solutioning & estimations

Knowledge, Skills and Abilities

Education

• Bachelor’s degree in computer science, information technology or equivalent educational qualification
• Technical Skills and Ex
• 8-10+ years of relevant experience
• SQL, data profiling, data validation, data storage and retrieval principles for Azure, Hadoop, document databases and RDMBS databases
• Data warehouses, data marts, data lakes, Medallion architecture
• Communication and structured problem-solving skills.,
• Domain based design
• Mentorship experience
• Storytelling skills, Partner & Stakeholder engagement experience
• Good to Have (Preferred)
• Data modeling tools such as Erwin
• Databricks, serverless SQL

Data Governance, Data Quality

Exposure to Gen AI technology and tools

Banking Financial Services and Insurance domain knowledge