Lead software Engineer

Role:- The MetLife Corporate Technology (CT) organization is evolving to enable MetLife’s New Frontier strategy. With a strong vision in place, we are a global function focused on driving digital technology strategies for key corporate functions within MetLife including, Finance, Actuarial, Reinsurance, Legal, Human Resources, Employee Experience, Risk, Treasury, Audit and Compliance. In partnership with our business leaders, we develop and deliver seamless technology experiences to our employees across the entire employee lifecycle. Our vision and mission is to create innovative, transformative and contemporary technology solutions to empower our leaders and employees so they can focus on what matters most, our customers. We are technologists with strong business acumen focused on developing our talent to continually transform and innovate. As part of Tech Talent Transformation (T3) agenda, MetLife is establishing a Technology Center in India. This technology center will perform as an integrated organization between onshore, offshore, and strategic vendor partners in an Agile delivery model. Responsibilities:- Participates in the design of architecture specifications leveraging Databricks and cloud-based data platforms, ensuring scalability, performance, and seamless integration with existing data ecosystems. Leads the collection and documentation of business and data requirements, translating them into user stories and technical solutions using Databricks workflows in collaboration with Product Owners. Owns detailed technical design and development of data pipelines, workflows, and analytics solutions on Databricks. Partners with Product Owners in sprint planning and delivery. Responsible for building and maintaining scalable data processing components using Databricks (e.g., Spark, Delta Lake) for batch and real-time data processing. Reviews solution architectures, data models, and code to ensure adherence to best practices, performance optimization, and data governance standards. Investigates and resolves production incidents related to data pipelines, platform performance, and data quality in Databricks environments. Prioritizes and manages incidents, defects, and service requests related to data platforms, collaborating with Product Owners and stakeholders. Identifies opportunities to optimize performance and cost efficiency of Databricks workloads; supports upgrades, migrations, and platform enhancements. Stays current with trends in data engineering, Databricks innovations, and cloud technologies; evaluates and promotes new tools and capabilities to enhance product features and customer outcomes.