Lead Data Engineer

The Lead Data Engineer plays a critical role in big data development within the data analytics engineering organization of MetLife Data & Analytics. This position has the responsibility for architecture & design of data and analytics solutions, building ETL, data warehousing, and reusable components using cutting-edge big data and cloud technologies. The role is based in Cary, NC, Tampa, FL, Wilmington, DE, Bridgewater, NJ, or NYC, NY, and supports MetLife's commitment to data-driven decision-making and operational excellence., * Design and execute a large-scale data migration initiative with a focus on defining migration architecture, ensuring data quality, and data reconciliation from various sources for consumption and reporting for analytics.

• Ingest huge volumes of data from various platforms for Analytics needs and write high-performance, scalable, reliable, and maintainable pipelines in Azure data bricks, Azure Data Factory, and related services.

• Developing reusable frameworks to manage complex data transformations, Validations, and data reconciliations.

• Develop quality code with thought-through performance optimizations in place right at the development stage.

• Appetite to learn new technologies and be ready to work on new cutting-edge cloud technologies.

• Work with teams spread across the globe in driving the delivery of projects and recommend development and performance improvements.

• Extensive experience with various database types and knowledge to leverage the right one for the need.

• Strong understanding of data tools and ability to leverage them to understand the data and generate insights

• Hands-on experience in building/designing at-scale Data Lake, Data warehouses, data stores for analytics consumption on Cloud platforms (real-time as well as batch use cases).

• Utilize Cloud technologies (preferably Azure Databricks) to enable PaaS-centric enterprise solutions.

• Implement solutions that support dynamic scaling, including throttling and bursting for high-volume data workloads.

• Establish and evangelize modern software development practices, including CI/CD, automated testing, and code quality standards

• Develop and support an API catalog for data services, ensuring standardization and security.

• Optimize reusable frameworks, Spark jobs for performance and cost efficiency in large-scale environments.

• Ability to interact with business analysts and functional analysts in getting the requirements and implementing ETL solutions.

• Bachelor's/ master's degree in information technology/computer science or a relevant domain.

• Microsoft Azure Certifications and/or Databricks certifications.

• 10+ years of solutions development and delivery experience with 6+ years of recent experience in data engineering.

• Strong analytic skills related to working with unstructured datasets.

• Data architecture (traditional - examples include SQL Server + modern - examples include Azure) and knowledge of data architecture patterns.

• Strong experience in Azure data bricks, including Spark, Delta Lake, data stores for analytics consumption (real-time as well as batch use cases)

• Ability to interact with business analysts and functional analysts in getting the requirements and implementing the ELT solutions.

• Proficiency and extensive experience with Spark/Scala/Python and performance tuning

• Experience with APIs and web services for data exchange

• Hands-on expertise in building & implementing data ingestion, curation, and data integration processes developed using Cloud data tools such as Azure Databricks, SQL, Azure Data Factory, Spark (Scala/Python), Delta Lake, etc.

• Performance tuning on Azure data bricks, dedicated SQL Pool and server SQL Pools, APIs loading and consumption optimizations.

• Very good problem solver and excellent communication skills - both written and verbal

Preferred:

• Experience using data reconciliation frameworks and data migration automation tools.

• Good scripting experience primarily on shell/bash/ PowerShell would be desirable.

• Experience in large-scale ERP transformation programs.

• Code versioning experience using Azure DevOps. Working knowledge of Azure DevOps pipelines.

• Prior experience leveraging AI and ML capabilities to automate and optimize complex workflows with intelligent use of low or no-code.

The MetLife Corporate Functions Data Office is part of the Data and Analytics Organization (D&A) within GTO. Our mission is to implement scalable data solutions for our stakeholders to generate actionable insights. We partner with Technology, and our Business and functional partners, to build and deploy the next generation data solutions for MetLife as we head into our New Frontier strategy!, At MetLife, we're leading the global transformation of an industry we've long defined. United in purpose, diverse in perspective, we're dedicated to making a difference in the lives of our customers.