Required Skills:

Academic Background: Bachelor’s degree with up to 2 year of relevant work experience Strong Hive, SQL skills, knowledge of Big data and related technologies Hands on experience on Hadoop & Shell Scripting is a plus Understanding of Data Architecture & Data Engineering concepts Strong verbal and written communication skills, with the ability to cater to versatile technical and non-technical audience Willingness to Collaborate with Cross-Functional teams to drive validation and project execution Good to have skills - Python / Py-Spark Excellent Analytical & critical thinking with attention to detail Excellent planning and organizations skills including ability to manage inter-dependencies and execute under stringent deadlines Exceptional drive and commitment; ability to work and thrive in in fast changing, results driven environment; and proven ability in handling competing priorities

Develop and Maintain Organized Data Layers to cater for both Production use cases and Analytics for Transaction Monitoring of Anti-Money Laundering rules.
Manage end to end Big Data Integration processes for building key variables from disparate source systems with 100% accuracy and 100% on time delivery
Partner closely with Strategy and Modeling teams in building incremental intelligence, with strong emphasis on maintaining globalization and standardization of attribute calculations across portfolios.
Partner with Tech teams in designing and building next generation data quality controls.
Drive automation initiatives within existing processes and fully optimize delivery effort and processing time
Effectively manage relationship with stakeholders across multiple geographies
Contribute into evaluating and/or developing right tools, common components, and capabilities
Follow industry best agile practices to deliver on key priorities
Ensuring process and actions are logged and support regulatory reporting, documenting the analysis and the rule build in form of qualitative document for relevant stakeholders.