What We Do
At Goldman Sachs, our Engineers don't just make things we make things possible. Our software is paramount to connecting people and capital with ideas. We solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets
.
Goldman Sachs Asset & Wealth Management
As one of the worlds leading asset managers, our mission is to help our clients achieve their investment goals. To best serve our clients diverse and evolving needs, we have built our business to be global, broad and deep across asset classes, geographies and solutions.Goldman Sachs Asset & Wealth Management is one of the worlds leading asset management institutions. AWM delivers innovative investment solutions managing close to Two Trillion US Dollars on a global, multi-product platform. In addition to traditional products (e.g. Equities, Fixed Income) our product offering also includes Hedge Funds, Private Equity, Fund of Funds, Quantitative Strategies, Fundamental Equity and a Multi-Asset Pension Solutions Business. Software is engineered in a fast-paced, dynamic environment, adapting to market and customer needs to deliver robust solutions in an ever-changing business environment. AM Data Engineering builds on top of cutting edge in-house and cloud platforms complimented with a strong focus on leveraging open source solutions.
Client Service Engineering is part of Asset Management Division we are responsible for providing the technology that powers AWM's award-winning client service organization. We operate as a full-stack team, and engineers contribute code in multiple languages on a variety of applications.
Job Summary
You will be a member of one of our teams in Dallas, who specialize in managing customer data and providing API's for other teams to consume. You will work with groundbreaking technologies and apply large-scale computing, distributed systems, data pipelining, workflow orchestration, restful APIs, and statistical algorithm techniques to solve the problems. To be successful, you will need to keep our long-term objectives in mind while contributing through short-term assignments. You are comfortable with ambiguity and are always open to identifying alternative paths. You will be as happy getting into code-level details as you are with coming up with a long-term vision for the team, and managing our various stakeholders.
We at Goldman Sachs embrace our differences. We are consciously building a culture of inclusion. We embed our culture of inclusion in our business principles we believe we must reflect the diversity of the communities and cultures in which we operate. That means we must attract, retain, and motivate people from many backgrounds and perspectives. Being diverse is not optional it is what we must be.
Inclusive team culture
Our team values work-life balance and deliberately tries to achieve a healthy balance between your personal and professional life. We collectively work towards building our project plans to fit the project tasks within the work hours.
Work/Life Balance
Basic qualifications
- Master's or bachelor's degree in computer science, or related numerical/engineering field.
- Interest and professional experience in data processing at scale.
- Strong, self-motivated individual with analytical mindset who can multi-task to solve interesting and difficult technical problems under time pressure and resource constraints.
- Adaptability and willingness to learn open to contributing across the stack.
Preferred qualifications
- Experience with Java development and other programming languages experience in Object Oriented analysis, design and testing best practices.
- Knowledge of SQL and no-SQL databases (e.g. Mongo, Elastic).
- Experience working with cloud AWS, GCP, etc.
- Excellent written and verbal communication skills, including experience working directly with both technical and non-technical stakeholders