Reference data; Vendor integrations and data pipelines; Data quality controls and governance; graph databases

RFQ workflow automation; portfolio risk management; trading platforms.

I have been a core part of the Voice Compliance Tech team at Goldman Sachs that has made it possible for Compliance Officers to carry out due-diligence on employee's phone calls by using text-based searching (regular expression) on a web interface as opposed to having to listen to multiple call recordings in their entirety.

My major contributions have been around the data delivery and exposure. I implemented significant parts of our new data ingestion pipeline using the Kafka Streams Java API in order to allow us transition from a high-latency, batch-based pipeline, to a near real-time one. I also implemented several of the services that allow user's to perform text-based searching on calls and listen to segments of the call's audio.

I have driven the reporting strategy within the Communications Compliance group of the company from both an application development and system design perspective. Some of progress we have made since I got involved include reducing the turn around time for complex reports from a matter of days to a matter of hours, Increasing the frequency of reporting (faster report data refresh cycles) and reporting on data points that were once not feasible due to the scale of data that we work with.

This was achieved by building out a hadoop-reporting infrastructure primarily in Scala that leverages Spark, Sqoop and Hive, and then plugging in some Java based reporting micro-services to this infrastructure.

ALSO: Contributed to the development of the new client on-boarding web application

TA for EE90 & EE91 (Experimental Projects in Electronic Circuits)