Design, build, and maintain scalable ETL/ELT pipelines on Azure or on-prem for batch and real-time processing. Monitor and optimize pipelines, ensure data quality, security and compliance, collaborate with business and D&A partners, implement DevOps CI/CD, and support data warehousing, lakes, and medallion architectures.
Description and Requirements
GG10.2 Data Engineer 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 Big Data, Engineering and Cloud expertise.It is an individual contributor role, expected to independently function 5-8+ years of relevant experience Bachelors degree in computer science, information technology or equivalent educational qualification • 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) • SQL, Python/Scala• NoSql and distributed databases (Hbase, Cosmos DB)• ETL pipleine development• Big Data Frameworks : Apache Spark, Hadoop, Hive• Cloud platforms: Azure data factory, Eventhub, Azure functions, Synapse, Databricks• Datawarehouses, data marts, data lakes• Medallion architecture• 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.,• Partner, Stakeholder engagement experience • DevOps practices: Git, AzureDevops, CI/CD pipelines• Unix shell scripting, MongoDB, Nifi• Exposure to Gen AI technology and tools
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.
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
GG10.2 Data Engineer 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 Big Data, Engineering and Cloud expertise.It is an individual contributor role, expected to independently function 5-8+ years of relevant experience Bachelors degree in computer science, information technology or equivalent educational qualification • 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) • SQL, Python/Scala• NoSql and distributed databases (Hbase, Cosmos DB)• ETL pipleine development• Big Data Frameworks : Apache Spark, Hadoop, Hive• Cloud platforms: Azure data factory, Eventhub, Azure functions, Synapse, Databricks• Datawarehouses, data marts, data lakes• Medallion architecture• 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.,• Partner, Stakeholder engagement experience • DevOps practices: Git, AzureDevops, CI/CD pipelines• Unix shell scripting, MongoDB, Nifi• Exposure to Gen AI technology and tools
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.
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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