• Design, build, and optimize scalable ETL/data pipelines on Azure Databricks • Automate data workflows using Azure Data Factory, Databricks, PySpark, and related Azure services • Integrate diverse data sources into data lakehouse and data warehouse solutions to enable advanced analytics • Design SQL Warehouse views and data models for downstream consumption and analytics use cases • Translate complex business requirements into scalable, reliable data products • Enhance, troubleshoot, and maintain cloud‑based data pipelines to ensure performance, reliability, and data quality • Collaborate with cross‑functional teams and contribute to timely delivery of data solutions

Description and Requirements Position Summary MetLife established a Global capability center (MGCC) in India to scale and mature Data & Analytics, technology capabilities in a cost-effective manner and make MetLife future ready. The center is integral to Global Technology and Operations with a 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 Senior Big 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. 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) ` Education Bachelor's degree in computer science, information technology or equivalent educational qualification Experience (In Years) 8-11+ years of relevant experience Technical Skills • SQL, Python/Scala • NoSQL and distributed databases (Hbase, Cosmos DB) • ETL pipeline 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 pipelines with Spark • Communication skills, analytical skills, structured problem-solving skills., • Partner, Stakeholder engagement experience Preferred skills • 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

• Create and deploy data pipelines • Work in a collaborative environment • Tackle diverse challenges • Empower people through data

• Design, implement, and maintain complex data pipelines, ensuring scalability and reliability using Airflow, dbt, Rivery, Python, and SQL, enabling robust ingestion and transformation of structured and semi-structured data. • Serve as a strategic partner to business teams, working closely with stakeholders to translate high-level goals into data solutions that support forecasting, performance tracking, and optimization. • Develop and maintain clean, well-documented data models in Snowflake and BigQuery that support analytics, reporting, and operational workflows and contribute to architecture decisions. • Integrate data from a variety of internal and external sources, including Google Analytics and third-party APIs, to support full-funnel visibility across departments. • Enable self-service analytics by ensuring data assets are discoverable and usable via tools such as Tableau, including thoughtful semantic layer design and performance tuning. • Contribute to the development of robust monitoring and observability practices for data quality and pipeline health. • Collaborate on architecture and design decisions, including cloud infrastructure and containerization using AWS. Pulumi and Docker. • Maintain strong documentation and promote engineering standards that ensure transparency, maintainability, and reusability of data systems.