Senior Software Engineer leading the platform uplift and modernization efforts for the Reconciliations platform at Goldman Sachs

• Senior Software Engineer for data platform providing ETL for 1000+ upstream feeds & reconciliations for 30+ user groups

• Lead modernization efforts of the platform migrating from monolith into Service Oriented microservices architecture (SoA) on Kubernetes clusters

• Establish contracts between services and define data models to represent flow of data in the system

• Deliver data distribution as a service unifying & standardizing data, enabling subscription model for clients & partner teams

• Identify data opportunities working with Business and operations building solutions to influence product and drive impact.

• Use Java Dropwizard framework and build high performant independent RESTful microservices for components

• Deliver Data distribution as a service improving data categorization, modelling & tracking user-actions on data

• Build service ingesting data into HDFS laying foundation for the platform to be available on Datalake

• Mentor junior engineers, conduct code reviews advocating industry practices, fostering innovation & creativity

• Execute large initiatives using agile methodologies to manage timelines, breakdown tasks and sprint planning

• Create Dropwizard starter packages and plug & play libraries providing HTTP operations and H2-integrated testing models

• Senior developer and Primary owner for the persistence component for the Reconciliations platform

• Implemented auto retry mechanism for persistence service decreasing failures by 20% across platform

• Use Shell and DB2 command line to build tools to migrate data into new platform orchestrating through RPC calls

• Migrated ETL from files into real-time improving holiday processing, reducing incidents annually by 30%

• Use Sci-kit libraries to build dashboards identifying control points eligible for migration from regression results

• Participate in on-call rotation, troubleshoot to mitigate critical incidents, and avoid or reduce business impact

• Following up with Root Cause Analysis (RCA), documentation, and tactical and strategic fixes

• Identify data opportunities working with Business and building solutions to influence product and drive impact

• Primary owner for data collection, management and processing of power outages complaint data at New York City

• Collected data using web crawlers providing data points to a real-time geospatial map in 15-minute intervals

• Built web crawlers using Selenium drivers and Python Scrapy and processed data on the fly for streaming & persistence

• Implemented distributed style crawling using Python multiprocessing to reduce the overall crawling time by 75%

• Developed a queueing mechanism to control the distribution level based on the number of cores available using Redis

• Performed batch processing with Pyspark to process 8 million data points outage complaints for downstream analysis