GOLDMAN SACHS ENGINEERING CULTURE

At Goldman Sachs, our Engineers don’t just make things – we make things possible. Change the world by connecting people and capital with ideas. 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.

Engineering is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions. Want to push the limit of digital possibilities? Start here!

Who we look for:

You are a proven full stack engineer. Not only strong technically, you have shown that you can work effectively with product managers, designers and other engineering teams.
You have a fierce sense of ownership, caring deeply about the quality of everything that you deliver into your clients’ hands.
You love the challenge of engineering and are confident in your ability to bring clarity and direction to ambiguous problem spaces.
You work well in a fast-paced environment while deeply invest in long term quality and efficiency.
Basic Qualifications
1-4 years of hands-on development experience in Core Java (Java 11-21) or Python, and proficiency in backend technologies such as Databases (SQL/No-SQL), Elastic Search, MongoDB, Spring framework, REST, GraphQL, Hibernate, etc.
Experience with front-end development with React, Redux, Vue, Typescript, and/or similar frameworks.
Demonstrated experience operating in a fast-paced Agile/Scrum setup with a global/remote team.
Knowledge of developing and deploying applications in public cloud (AWS, GCP or Azure) or K8S.
Experience with implementing unit tests, integration tests, Test Driven Development.
Strong development, analytical and problem-solving skills.
Knowledge of prompt engineering, LLM, AI Agents, etc.
Preferred Qualifications

Excellent communication skills and experience working directly with business stakeholders.
Data modeling, warehousing (Snowflake, AWS Glue/ EMR, Apache Spark ) and a strong understanding of data engineering practices.
Technical, Team or Project leadership experience.
Some experience using Infrastructure-As-Code tools (e.g. AWS CDK, Terraform, CloudFormation)
Experience with reactive, event-based architectures.