This Design and build high performing and scalable data pipeline platform using Hadoop, Apache Spark, MongoDB and object storage architecture.
Design and build the data services on container-based architecture such as Kubernetes and Docker
Partner with Enterprise data teams such as Data Management & Insights and Enterprise Data Environment (Data Lake) and identify the best place to source the data
Work with business analysts, development teams and project managers for requirements and business rules.
Collaborate with source system and approved provisioning point (APP) teams, Architects, Data Analysts and Modelers to build scalable and performant data solutions.
Effectively work in a hybrid environment where legacy ETL and Data Warehouse applications and new big-data applications co-exist
Work with Infrastructure Engineers and System Administrators as appropriate in designing the big-data infrastructure.
Work with DBAs in Enterprise Database Management group to troubleshoot problems and optimize performance
Support ongoing data management efforts for Development, QA and Production environments
Utilizes a thorough understanding of available technology, tools, and existing designs.
Leverage knowledge of industry trends to build best in class technology to provide competitive advantage.
Acts as expert technical resource to programming staff in the program development, testing, and implementation process