Designs, builds, maintains, monitors, and optimizes cloud and on-premises ETL/ELT pipelines for large-scale batch and real-time data processing. Ensures data quality, security, compliance, reliability, and performance. Leads solution design and estimation, collaborates with business and technology stakeholders, and mentors data engineers. Uses Azure, big data frameworks, distributed databases, data lakes, warehouses, streaming technologies, and medallion architecture.
Description and Requirements
MGCC GG 11.1- Senior Big Data Engineer I
Position Title:
MGCC GG 11.1 - Senior Big Data Engineer I
Function, Responsibility Level:
Reports to (Responsibility Level): GG 12 or above
Supervises:
GG 10.1 - Big Data Engineer I
GG 10.2 - Big Data Engineer II
Location:
Global Grade: 11
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. This role mentors Data engineers. It is an individual contributor role, expected to solve wide ranging business problems,
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
• 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)
• Mentor Data Engineers
• 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 Experience
• 8-10+ 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
• Datawarehouse's, data marts, data lakes
• Medallion architecture
• Performance tuning, optimization, and data quality validation
• Real-time and batch data processing, streaming pipelines with Spark
• Communication skills, analytical skills, structured problem-solving skills, mentorship skills
• Mentorship experience
• Storytelling skills, Partner & Stakeholder engagement experience
Good to Have (Preferred)
• DevOps practices: Git, AzureDevops, CI/CD pipelines
• Unix shell scripting, Kafka, MongoDB, Nifi
• Exposure to Gen AI technology and tools
• Banking Financial Services and Insurance domain knowledge
About MetLife
Recognized on Fortune magazine's list of the "World's Most Admired Companies" and Fortune World's 25 Best Workplaces™, MetLife, through its subsidiaries and affiliates, is one of the world's leading financial services companies; providing insurance, annuities, employee benefits and asset management to individual and institutional customers. With operations in more than 40 markets, we hold leading positions in the United States, Latin America, Asia, Europe, and the Middle East.
As part of our New Frontier strategy, MetLife is building an AI-enabled, people-centered future. We're looking for people who bring curiosity, adaptability, and a growth mindset as we use AI to enhance how we serve customers, support communities, and evolve the way work gets done. At MetLife, AI is a responsible partner that supports human judgment, creativity, and continuous improvement while helping us build trust, inclusion, and long-term value.
Our purpose is simple - to help our colleagues, customers, communities, and the world at large create a more confident future. United by purpose and guided by our core values - Win Together, Do the Right Thing, Deliver Impact Over Activity, and Think Ahead - we're inspired to transform the next century in financial services. At MetLife, it's #AllTogetherPossible . Join us!
#BI-Hybrid
MGCC GG 11.1- Senior Big Data Engineer I
Position Title:
MGCC GG 11.1 - Senior Big Data Engineer I
Function, Responsibility Level:
Reports to (Responsibility Level): GG 12 or above
Supervises:
GG 10.1 - Big Data Engineer I
GG 10.2 - Big Data Engineer II
Location:
Global Grade: 11
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. This role mentors Data engineers. It is an individual contributor role, expected to solve wide ranging business problems,
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
• 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)
• Mentor Data Engineers
• 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 Experience
• 8-10+ 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
• Datawarehouse's, data marts, data lakes
• Medallion architecture
• Performance tuning, optimization, and data quality validation
• Real-time and batch data processing, streaming pipelines with Spark
• Communication skills, analytical skills, structured problem-solving skills, mentorship skills
• Mentorship experience
• Storytelling skills, Partner & Stakeholder engagement experience
Good to Have (Preferred)
• DevOps practices: Git, AzureDevops, CI/CD pipelines
• Unix shell scripting, Kafka, MongoDB, Nifi
• Exposure to Gen AI technology and tools
• Banking Financial Services and Insurance domain knowledge
About MetLife
Recognized on Fortune magazine's list of the "World's Most Admired Companies" and Fortune World's 25 Best Workplaces™, MetLife, through its subsidiaries and affiliates, is one of the world's leading financial services companies; providing insurance, annuities, employee benefits and asset management to individual and institutional customers. With operations in more than 40 markets, we hold leading positions in the United States, Latin America, Asia, Europe, and the Middle East.
As part of our New Frontier strategy, MetLife is building an AI-enabled, people-centered future. We're looking for people who bring curiosity, adaptability, and a growth mindset as we use AI to enhance how we serve customers, support communities, and evolve the way work gets done. At MetLife, AI is a responsible partner that supports human judgment, creativity, and continuous improvement while helping us build trust, inclusion, and long-term value.
Our purpose is simple - to help our colleagues, customers, communities, and the world at large create a more confident future. United by purpose and guided by our core values - Win Together, Do the Right Thing, Deliver Impact Over Activity, and Think Ahead - we're inspired to transform the next century in financial services. At MetLife, it's #AllTogetherPossible . Join us!
#BI-Hybrid
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Designs, builds, and maintains scalable ETL/ELT pipelines for batch and real-time processing across Azure and on-premises environments. Ensures pipeline reliability, performance, data quality, security, and compliance. Collaborates with business and technology stakeholders, leads solution design and estimation, troubleshoots data platforms, and mentors data engineers. Uses Big Data frameworks, distributed databases, cloud services, data lakes, warehouses, streaming technologies, and DevOps practices.
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Designs, builds, maintains, and optimizes production-grade batch and real-time data pipelines across Azure and on-premises environments. Handles large structured and unstructured datasets using big data frameworks, distributed databases, streaming technologies, and cloud services. Ensures data quality, security, compliance, reliability, and scalability. Partners with business and technology teams, leads solution design and estimations, mentors data engineers, and contributes to analytics and data governance initiatives.
Top Skills:
Apache NifiSparkAzureAzure Data FactoryAzure DevopsAzure Event HubsAzure FunctionsAzure SynapseCi/CdCosmos DbData LakesData MartsData WarehousesDatabricksEltETLGen AiGitHadoopHbaseHiveKafkaMedallion ArchitectureMongoDBNoSQLPythonScalaSQLUnix Shell Scripting
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