Communicate with business users and conduct thorough study and analysis of client’s data and business processes to gather, identify, and ascertain its needs and requirements in business intelligence (BI) analysis.  Responsible and accountable for data requirements in terms of sourcing, analyzing, processing, and delivering data.  Perform data extraction, transformation, manipulation, and refinery of customer related data, and move data between production systems and across multiple platforms.  Perform segmentation analytics for each campaign using database technologies present both on premise (such as SQL, Teradata, UNIX) and on cloud platform using AWS (Amazon Web Services) technologies and Big Data technologies such as Spark, Cassandra, Python, and Redshift.  Work on SAS programs in understanding the current logic and to convert to newer technologies using Python, SQL, and AWS.  Perform data sanity check and quality check through data pipelines by designing and executing validation test cases.  Drive statistical analytics, post processing, and result reporting to the leadership team using Tableau, Elk, Python, and GraphX libraries.  Build insights out of exploratory data analysis on a multi-dimensional data layer to study attrition modelling and other advanced analytics use cases for strategic decision making, using Python Machine Learning APIs such as scikit-learn and advanced SQL.  Build analytics infrastructure for big data processing on AWS cloud platform to streamline and automate recurring campaigns by scheduling data processing clusters that perform data segmentation, data hand off, and statistical analytics required for result reporting.  Deliver Snowflake tables and Tableau dashboards.  Automate daily and weekly refresh of tables by scheduling those in UNIX, seamlessly updating Tableau dashboards.