Risk-Salt Lake City-Software Engineering

Overview

To ensure uncompromising accuracy and timeliness in the delivery of critical risk metrics that support Goldman Sachs' decision making process, our data platform is continuously growing and evolving. 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 business transaction we engage in. Risk Engineering has an opportunities for an Analyst & Associate level Software Engineers to work across a broad range of applications and extremely diverse set of technologies to keep the platform operating at peak efficiency.

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 global 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, Cloud computing, HDFS, Spark, S3, ReactJS, Sybase IQ, Snowflake, Tableau 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.

• This role is for a Developer in large projects across a global team of developers and risk managers
• You will apply your prior experience and expertise of working in credit risk domain at a large bank or financial institution, and ramp up very quickly to work with the global team
• Performance tune applications to improve memory and CPU utilization.
• Perform statistical analyses to identify trends and exceptions related Market Risk metrics.
• Build internal and external reporting for the output of risk metric calculation using data extraction tools, such as SQL, and data visualization tools, such as Tableau.
• Utilize web development technologies to facilitate application development for front end UI used for risk management actions
• Develop software for calculations using databases like Snowflake, Sybase IQ and distributed HDFS systems.
• Interact with business users for resolving issues with applications.
• Design and support batch processes using scheduling infrastructure for calculation and distributing data to other systems.
• Oversee junior technical team members in all aspects of Software Development Life Cycle (SDLC) including design, code review and production migrations.

• Bachelor's degree in Computer Science, Mathematics, Electrical Engineering or related technical discipline
• 1-5 years' experience working with risk technology teams in a large investment or retail bank, or a comparable financial institution.
• Experience in credit risk management functions and processes, knowledge of major regulatory deliverables for risk and expertise in related technology is required
• Experience in software development, including a clear understanding of data structures, algorithms, software design and core programming concepts
• Comfortable multi-tasking, managing multiple stakeholders and working as part of a team
• Comfortable with working with multiple programming languages, including learning proprietary software coding when required
• Technologies: Scala, Java, Python, Spark, Linux and shell scripting, TDD (JUnit), build tools (Maven/Gradle/Ant)
• Experience with one or more major relational / object databases.
• Experience in working with process scheduling platforms like Apache Airflow.
• Should be ready to work in GS proprietary technology like Slang/SECDB
• An understanding of compute resources and the ability to interpret performance metrics (e.g., CPU, memory, threads, file handles).
• Knowledge and experience in distributed computing - parallel computation on a single machine like DASK, Distributed processing on Public Cloud.
• Knowledge of SDLC and experience in working through entire life cycle of the project from start to end