Description and Requirements

GG12.1 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. The role requires one to demonstrate Big Data, Engineering and Cloud expertise. Expected to be highly proficent at technical skills. Besides contributing in individual capacity, this role also leads and develops Data and Analytics talent Experience 12-14+ years of relevant experience Education Bachelors degree in computer science, information technology or equivalent educational qualification 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 Technical Skills • SQL, Python/Scala
• NoSql and distributed databases (Hbase, Cosmos DB)
• ETL pipleine 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 • 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

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!