Lead I - Software Engineering - Scala Spark

UST is a leading provider of platforms; digital innovation; artificial Intelligence and end-to-end IT services and solutions for Global 1000 companies. We are transforming corporations through deep domain expertise; knowledge-based ML platforms; as well as profound anthropological efforts to understand the end customer and design products and interactions that create delight. We are deeply committed to developing a comprehensive understanding of our clients problems and developing platforms to address them Responsibilities will include: Understand and implement tactical or strategic solution for a given business problem Discussion with stakeholders on business needs and technology requirements. Define and derive the strategic solutions as well as identify tactical solutions when necessary. Write technical design other solution documents per Agile (SCRUM) standards. Perform data analysis to aid development work and other business needs. Perform unit testing of the developed code leveraging automated BDD test framework. Participate in the testing effort to validate and approve technology solutions. Follow the MS standards for adoption of automated release process across environments. Perform automated regression test case suite and support UAT of developed solution. Work using collaborative technique with other FCT NFRT teams. Required Skills 5+ years of experience as a Hands On Scala/Spark developer Hands on SQL writing skills on RDBMS (DB2) databases Ability to perform code optimization for performance, Scalability and configurability Must have worked at least 2 years in a HDFS platform development project. Proficiency in data analysis, data profiling, and data lineage Strong oral and written communication skills Experience working in Agile projects. Desired Skills Understanding of Actimize ACTONE platform features. Understanding/Development on AZURE Cloud based implementation Knowledge of Behavior driven development (BDD) Possess Big data technology certification. Experience in Machine Learning, predictive Analytics