Senior Java Full Stack Developer

Key Qualifications & Experience Onsite Interview Must Java, Angular, AWS, PythonBig Data & Analytics:4+ years of experience with big data technologies such as Spark and HadoopStrong ability to bridge user-facing applications with large-scale data platforms (terabyte sized)Strong SQL skills (3+ years) for data analysis and performance optimizationAI Experience (Required) for productivity Role Focus & Impact Support and scale a new, fast-moving applicationBuild data-driven insights and analytics c

Responsibilities - Design and implementation of scalable big data pipelines for batch and real time processing - Build and operate streaming data platforms using Kafka - Design and deploy cloud native data solutions across AWS - Develop and manage containerized workloads using Kubernetes - Enable data mesh architecture with domain oriented data products - Design and implement data lake and lakehouse architectures - Ensure data quality, reliability, and observability - Implement governance capabi

As part of the Big Data Engineering and Analytics organization, this role will focus on enabling a modern data lake and data mesh architecture that supports high volume, high velocity, and high variety data across enterprise and platform domains. The Lead Data Engineer will bring deep hands-on expertise in Kubernetes, Kafka streaming platforms. This role partners closely with data architects, analytics teams, and platform engineering to deliver reliable, governed, and high-quality data solutions

Job Summary (List Format): - Lead the design and development of scalable big data applications using Python (10+ years' experience required). - Build and optimize efficient data processing pipelines with big data technologies such as Hadoop/EMR, Spark, and Hive. - Develop and maintain solutions leveraging AWS services, including Lambda, EventBridge, Step Functions, Redshift, S3, and Glue (5+ years' experience required). - Implement data transformation, manipulation, and analysis workflows, in