Big Data Engineer Lead

MGCC GG 12.1– Lead Big Data Engineer I

Position Title:

MGCC GG 12.1– Lead Big Data Engineer I

Function, Responsibility Level:

Reports to (Responsibility Level): GG 13 or above

Supervises:

GG 10.1 – Big Data Engineer I

GG 10.2 - Big Data Engineer II

GG 11.1 - Senior Big Data Engineer I

Location:

Global Grade: 12

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:

Data Engineer plays a critical role in data and analytics life cycle and significantly contributes to production grade data and analytics solutions. This role requires one to demonstrate Big Data, Engineering and Cloud expertise. Expected to be highly proficient at technical skills. Besides contributing in individual capacity, this role also leads and develops Data and Analytics talent

Job Responsibilities

Design, build, and maintain robust ETL/ELT pipelines on cloud(Azure) or on-prem to collect, ingest and store large volumes of structured and unstructured data for batch/real time processing
Solve complex business problems using data and advanced technologies
Monitor, optimize, and troubleshoot data pipelines to ensure reliability, scalability, and performance
Ensure data processing, quality, security, and compliance guidelines, policies and standards are followed
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)
Independently lead design, solutioning & estimations
Provide people leadership: coach, develop and engage talent

Knowledge, Skills and Abilities

Education

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

Technical Skills and Experience

12-14+ years of relevant experience

SQL, Python/Scala
NoSql and distributed databases (Hbase, Cosmos DB)
ETL pipeline design and development; Solutioning and estimation
Big Data Frameworks : Apache Spark, Hadoop, Hive
Cloud platforms: Azure data factory, Eventhub, Azure functions, Synapse, Databricks
Datawarehouses, data marts, data lakes
Medallion architecture, and other design patterns
Performance tuning, optimization, and data quality validation
Real-time and batch data processing , streaming pieplines with Spark
Communication skills, analytical skills, structured problem-solving skills,mentorship & people leadership skills
Storytelling skills , Partner & Stakeholder engagement experience
People leadership: talent development & engagement experience

Good to Have (Preferred)

DevOps practices: Git, AzureDevops, CI/CD pipelines
Unix shell scripting, MongoDB, Nifi
Lambda architecture, Kappa Architecture
Exposure to Gen AI technology and tools
Banking Financial Services and Insurance domain knowledge

MGCC GG 12.1– Lead Big Data Engineer I

Position Title:

MGCC GG 12.1– Lead Big Data Engineer I

Function, Responsibility Level:

Reports to (Responsibility Level): GG 13 or above

Supervises:

GG 10.1 – Big Data Engineer I

GG 10.2 - Big Data Engineer II

GG 11.1 - Senior Big Data Engineer I

Location:

Global Grade: 12

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:

Data Engineer plays a critical role in data and analytics life cycle and significantly contributes to production grade data and analytics solutions. This role requires one to demonstrate Big Data, Engineering and Cloud expertise. Expected to be highly proficient at technical skills. Besides contributing in individual capacity, this role also leads and develops Data and Analytics talent

Job Responsibilities

Design, build, and maintain robust ETL/ELT pipelines on cloud(Azure) or on-prem to collect, ingest and store large volumes of structured and unstructured data for batch/real time processing
Solve complex business problems using data and advanced technologies
Monitor, optimize, and troubleshoot data pipelines to ensure reliability, scalability, and performance
Ensure data processing, quality, security, and compliance guidelines, policies and standards are followed
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)
Independently lead design, solutioning & estimations
Provide people leadership: coach, develop and engage talent

Knowledge, Skills and Abilities

Education

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

Technical Skills and Experience

12-14+ years of relevant experience

SQL, Python/Scala
NoSql and distributed databases (Hbase, Cosmos DB)
ETL pipeline design and development; Solutioning and estimation
Big Data Frameworks : Apache Spark, Hadoop, Hive
Cloud platforms: Azure data factory, Eventhub, Azure functions, Synapse, Databricks
Datawarehouses, data marts, data lakes
Medallion architecture, and other design patterns
Performance tuning, optimization, and data quality validation
Real-time and batch data processing , streaming pieplines with Spark
Communication skills, analytical skills, structured problem-solving skills,mentorship & people leadership skills
Storytelling skills , Partner & Stakeholder engagement experience
People leadership: talent development & engagement experience

Good to Have (Preferred)

DevOps practices: Git, AzureDevops, CI/CD pipelines
Unix shell scripting, MongoDB, Nifi
Lambda architecture, Kappa Architecture
Exposure to Gen AI technology and tools
Banking Financial Services and Insurance domain knowledge