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Senior Data Quality Analyst I
Actively Reviewing
MetLife
Job Description
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 Quality Analyst plays a critical role in data and analytics life cycle and significantly contributes to ensuring data quality of production grade data and analytics solutions. The role requires one to demonstrate expertise in data profiling, validation, data pipeline monitoring and quality reporting.This role mentors Data Quality Analysts. It is an individual contributor role, expected to solve wide ranging business problems, It is an individual contributor role.
Job Responsibilities
Education
Bachelor’s degree in computer science, information technology or equivalent educational qualification
Technical Skills And Experience
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 Quality Analyst plays a critical role in data and analytics life cycle and significantly contributes to ensuring data quality of production grade data and analytics solutions. The role requires one to demonstrate expertise in data profiling, validation, data pipeline monitoring and quality reporting.This role mentors Data Quality Analysts. It is an individual contributor role, expected to solve wide ranging business problems, It is an individual contributor role.
Job Responsibilities
- Build and maintain validation rules/test cases to ensure quality of data on variety of dimensions: accuracy, completeness, consistency and timeliness
- Perform DQ checks at various lifecycle stages e.g. (unit testing , intergration testing, user acceptance testing)
- Perform profiling to detect anomalies
- Create and maintain data quality artefacts
- Collaborate with multiple partners from Business, Technology, Operations and D&A capabilities (Data Governance, BSA, Data science, Data Platforms, BI)
- Independently lead design, solutioning & estimations
- Mentor DQ Analysts
- Collaborate with multiple partners from Business,Technology, Operations and D&A capabilities (Data Governance, Data Quality, Data Modeling, Data Architecture, Data science, DevOps, BI & insights)
Education
Bachelor’s degree in computer science, information technology or equivalent educational qualification
Technical Skills And Experience
- 8-10+ years of relevant experience
- SQL
- Azure Data Services (data factory,synpase)
- Data quality testing tools such as Atacamma(web & Desktop), IDQ, ETL tools like Tosca
- Data profiling, cleansing and anomaly techniques
- Understand Datamart, Data lake and Data Warehouse
- Mentorship experience
- Experience working with large data states in On-Prem and Cloud environments
- Communication skills, analytical skills, structured problem-solving skills
- Storytelling, Partner, Stakeholder engagement experience
- Exposure to Gen AI technology and tools
- NO-SQL databases, HIVE
- Banking Financial Services and Insurance domain knowledge
Required Skills
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