Rahul

As a child, I had always thought that I would join the Indian military, just like my father. That changed, however, when I was in high school and I wrote my first piece of program in the Turbo C++ editor. I remember spending quite a few weekends writing my own programs in my notebook, then rushing to the school computer lab after class to input and tinker it to get it working. By the time I finished high school, I had made up my mind to pursue computer science and engineering for my bachelor’s degree. 

I joined Goldman Sachs in 2014 as an analyst on the Operations Strat team after spending a couple of years at a startup. It was during the interview process when I was really sold on a career at Goldman Sachs; I was amazed by the diverse background of the individuals I got a chance to interact with during my interviews. At the time, my department head was an MD and had a PhD in electrical engineering; my direct manager had a background of applied mathematics; I met other engineers from equally diverse backgrounds as well. I knew after the interview process that I was going to be part of something special. 

I am part of the Data Lake team within the Engineering Division. Data Lake is a centralized storage repository that holds huge amount of data, catalogued and ready to be consumed by different teams within the firm. Data Lake also facilitates the discoverability of the vast variety of the data that we have, and helps to share it across different teams as needed. As Data Lake engineers, we develop scalable data processing systems that can handle petabytes of data efficiently. A project that I recently worked on involved finding the optimal resource allocation for Data Lake ingestion jobs. Data Lake currently ingests tens of thousands of datasets on a daily basis, each with varying size and shape. I prototyped a data-driven model that looks at 20-plus features of the data being ingested and dynamically calculates the optimal compute resources required for the ingestion. 

Engineering uniquely marries the creativity needed for an artist with the methodical problem solving skills of a scientist. There is something truly satisfying about finally cracking a complex problem that you have spent days working on. There is nothing routine about the work we do; each project brings its own unique problems to solve, and you never ever stop learning new things. It was during my post-graduation days at IIT Kanpur that I discovered my passion for data science. Finding patterns in huge amount of data was the perfect combination of problem solving and programming, and after graduation, I knew that was the kind of career that I wanted to build for myself. 

The scale of problems that engineers are given are some of the largest in the industry. From analyst to managing director, contributions that engineers have the ability to make towards solving these problems are endless. During my early days, so many individuals proactively helped me navigate these projects and opportunities. Now, as a vice president, I try my best to pay the debt forward by mentoring those junior to me wherever I can and make sure that they have as much of a voice in the room as I do. 

I have always enjoyed photography. I think one of the first things I bought with my first paycheck was a dSLR camera. Nowadays, I mostly do film photography. I appreciate the deliberateness of shooting film, as each shot needs to be carefully planned and executed. I also enjoy reading fantasy and exploring its secondary worlds; from Tolkien’s Middle Earth to Sanderson’s Roshar, and everything in between. 

The first few years of your career are the springboard for your future endeavors. Goldman Sachs always makes it a priority to invest in its people. Participate in the extended learning programs available to you for self-development, and more importantly, leverage the knowledge and experience of the people around you. And do not fear failures; if you ever have to choose between settling for inadequacy or risking a failure by striving to be the best, always choose the latter.