- Delivered on Big Data technologies like Apache Spark, Hadoop, HBase, Hive, Impala on Cloudera. Back-end batch processing using Scala 2.12 in Spark 2.1, storage using HDFS, NoSQL databases HBase and Impala, and scheduling using Control M the Big Data Universe was designed one to end- Modelled database HBase from a typical RDBMS environment - Worked with Spark Data Frames and optimised the SLA’s Managed data coming from different sources and involved in HDFS maintenance and loading of structured and unstructured data- Leading a team of eight, designed and built Data Warehouse for JPM Asset Management Compliance and worked on designing in- flow of data using Informatica from several source systems - Implemented around 80 rules that are applied on the various asset class trades to generate anomalies for Compliance team- While following Agile methodology, being the Product Owner of the team my day to day tasks include liaising with business for requirements and feedback, doing knowledge delivery sessions with team, keep track of sprint deliverables and at the same time be involved in active development of sprint tasks which can be Big Data tasks, Informatica ETL development, Stored Procedures or UNIX scripting- Worked on building Data Warehouse and reporting for Global Trade Surveillance for JPM Asset Management- Designed ETL flow for Global incoming feed sources and involved in active development of the same using Informatica- Developed numerous reports using Oracle PL/SQL and handled user queries and data issues- Worked actively on Informatica and Oracle/Sybase Stored Procedures to get feeds loaded into Data Warehouse and get reports generated for US Surveillance- Worked extensively on on-boarding APAC Trade Surveillance with a vision to expand Trade Surveillance globally

- Analyze the total impact of GPA on the data warehouse and come up with ETL, DB components which would be modified as part of it.- Discussions with clients and business users on the type and format of data that would be received and finalizing the requirements from ETL perspective.- Working on scripts for database changes.- Development and testing of ETL components.- Testing of the data loaded keeping in mind the business logic behind various fields of warehouse.- Training team on various aspects of the project.- Migrating the code to production environment and conducting knowledge transfer sessions for the support team