MetLife

At MetLife, data isn’t just a tool - it is a catalyst for growth. As part of our Data & Analytics organization, you’ll unlock trusted insights that drive bold decisions, power personalized customer experiences, and deliver lasting business impact. Your skills in AI, predictive modeling, and advanced analytics will help solve complex challenges, scale solutions globally, and fuel innovation across every region. We’re building the future of data - one that’s governed responsibly, engineered for scalability, and designed for growth. When you join us, you’re not just supporting the business - you’re empowering it. Let’s transform insight into impact and data into action, together.

The Data Engineer is responsible for designing, building, and maintaining production-grade ETL/ELT data pipelines and analytics-ready data products that power MetLife’s data and analytics ecosystem across our global Data & Analytics organization. This is an exciting opportunity to apply your Big Data, engineering, and Databricks/cloud expertise as an individual contributor, working closely with a project team to deliver reliable, scalable, and trusted data solutions.

• Design, build, and maintain robust ETL/ELT pipelines and reusable data assets (batch and near-real-time) on Databricks and Azure cloud or on-premises environments to ingest, transform, and publish curated, analytics-ready data
• Partner with data modelers, Data Governance, and Data Architecture teams to implement scalable dimensional data models (star schemas) and ensure solutions support downstream consumption in Power BI, Cognos, or similar BI tools
• Apply best practices for data ingestion, transformation, orchestration, and performance optimization, and contribute to migration from legacy pipelines to modern Databricks-based platforms
• Monitor, optimize, and troubleshoot data pipelines to ensure reliability, scalability, security, and compliance with data quality and governance standards
• Collaborate with a cross-functional project team, including Business, Technology, Operations, and Data & Analytics partners (Data Governance, Data Quality, Data Modeling, Data Architecture, Data Science, DevOps, BI & Insights), to deliver end-to-end solutions aligned with Agile/SAFe practices (PI planning, sprint execution)

• Bachelor's degree in Computer Science, Information Technology, Engineering, Mathematics, or a related field.
• 3–5 years of experience in data engineering, data integration, or a related technical discipline.
• Experience developing solutions using SQL and Python, Scala, or a similar programming language.
• Experience working with Databricks or comparable cloud data platform technologies.
• Experience with ETL/ELT development, data integration, and data transformation processes.
• Understanding of dimensional data modeling and data warehousing concepts.
• Experience working with cloud technologies such as Azure, AWS, or GCP.
• Strong analytical, troubleshooting, and problem-solving skills.
• Strong written and verbal communication skills.

• Experience with Azure Data Factory, Synapse, Event Hub, or comparable cloud-native data technologies.
• Experience with Spark, Hadoop, Hive, or other distributed data processing technologies.
• Familiarity with CI/CD tools, Git, and DevOps practices.
• Familiarity with data quality and governance concepts.
• Experience with Power BI, Cognos, Tableau, or similar reporting platforms.
• Experience working in Agile delivery environments.
• Exposure to financial services, insurance, or other regulated industries.

The expected salary range for this position is $103,000 - $133,000. This role may also be eligible for annual short-term incentive compensation and stock-based long-term incentives. All incentives and benefits are subject to the applicable plan terms.