Goldman Sachs Recruitment Drive 2025 | Goldman Sachs Hiring Software Engineer

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The Goldman Sachs Group, Inc., is an American multinational investment bank and financial services company.
It is headquartered in New York City and offers services in investment management, securities, asset management, prime brokerage, and securities underwriting.

To ensure uncompromising accuracy and timeliness in the delivery of the risk metrics, our platform is continuously growing and evolving.
Credit Risk Engineering combines the principles of Computer Science, Mathematics and Finance to produce large scale, computationally intensive calculations of risk Goldman Sachs faces with each transaction we engage in.

Bachelor’s degree in Computer Science, Mathematics, Electrical Engineering or related technical discipline with 6 months - 2 years of working experience
Willingness to learn new things and work with a diverse group of people across multiple geographical locations
An eagerness to grow as a Software Engineer
Proficiency in Java, Python or another Object-Oriented Programming language
A clear understanding of data structures, algorithms, software design and core programming concepts
Experience with one or more major relational / object databases including cloud databases like Snowflake
Interact with business users for resolving issues with applications.
Performance tune applications to improve memory and CPU utilization.

As an Engineer in the Risk Engineering organization, you will have the opportunity to impact one or more aspects of risk management.
You will work with a team of talented engineers to drive the build & adoption of common tools, platforms, and applications.
The team builds solutions that are offered as a software product or as a hosted service.
We are a dynamic team of talented developers and architects who partner with business areas and other technology teams to deliver high profile projects using a raft of technologies that are fit for purpose (Java, Python, Snowflake, Cloud Computing (AWS), S3, Spark, ReactJS, among many others).
A glimpse of the interesting problems that we engineer solutions for, include acquiring high quality data, storing it, performing risk computations in limited amount of time using distributed computing, and making data available to enable actionable risk insights through analytical and response user interfaces.