Hybrid Data Engineer - Databricks Cloud Pipelines

MetLife; Bridgewater (MA); Hybrid; USD 103,000 - 133,000; Full time

Benefits offered by this job

Health insurance

401(k) with employer matching

Paid time off

Job summary

MetLife is seeking a Data Engineer to design, build, and maintain production-grade ETL/ELT data pipelines and analytics-ready data products powering MetLife’s data ecosystem. This role emphasizes Databricks, Azure cloud, and scalable data solutions across our global organization.

The engineer will partner with governance, modeling, and BI teams to enable analytics via Power BI, Cognos, or similar tools, while ensuring data quality, security, and compliance. Hybrid role in the United States.

Qualifications

• 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.

Responsibilities

• 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).

Skills

SQL

Python

Scala

Big Data

Data modeling

Cloud platforms

Analytical thinking

Communication

Education

Bachelor's degree in Computer Science, Information Technology, Engineering, Mathematics

Tools

Databricks

Azure

AWS

GCP

Job description

MetLife is seeking a Data Engineer to design, build, and maintain production-grade ETL/ELT data pipelines and analytics-ready data products powering MetLife’s data ecosystem. This role emphasizes Databricks, Azure cloud, and scalable data solutions across our global organization.

The engineer will partner with governance, modeling, and BI teams to enable analytics via Power BI, Cognos, or similar tools, while ensuring data quality, security, and compliance. Hybrid role in the United States.