What We Do

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, which is comprised of core and business-aligned teams, 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.

About Data Engineering

Data plays a critical role in every facet of the Goldman Sachs business. The Data Engineering group is at the core of that offering, focusing on providing the platform, processes, and governance, for enabling the availability of clean, organized, and impactful data to scale, streamline, and empower our core businesses.

Within Data Engineering, we focus on offering a comprehensive data platform, Legend, which we have made available as an open-source product.  Legend includes a full data modeling environment, as well as the execution of data access and controls, and a vast set of value-add products which allow our business users to operate more efficiently. Engineers at Goldman use the Legend offering to build efficient data solutions that source, curate, and distribute critical data to our businesses, including financial product, pricing, transaction, and client reference data. 

Who We Look For

Goldman Sachs Engineers are innovators and problem-solvers, building solutions in risk management, big data, mobile and more. We look for creative collaborators who evolve, adapt to change and thrive in a fast-paced global environment.

As a Full-stack Software Engineer on the Data Engineering team, you will be responsible for improving the Legend data platform. We tackle some of the most complex engineering problems across optimizing data access and delivery, enabling core access controls via well-defined security paradigms, building UIs to enable data visualization/analytics/discovery/management, or engaging with the product team to ensure the firm’s data needs are met. We react quickly to new demands by rapidly evolving our data solutions.

How You Will Fulfill Your Potential 

• Design & develop data management tools to curate our most important data sets, models, and processes
• Contribute to an open-source technology - https://github.com/finos/legend

Relevant Technologies: Java, CSS, React

Basic Qualifications

• A bachelor’s or master’s degree in a computational field (Computer Science, Applied Mathematics, Engineering, or in a related quantitative discipline)
• 3 + years of experience with UX frameworks (React/Angular, TypeScript is a plus)
• 3+ years of relevant work experience in a team-focused environment
• 3+ years of experience using OO languages 
• 3+ years of experience in functional programming languages
• Strong object-oriented design and programming skills and experience in OO languages (Java, etc.)
• Strong skills in CSS with the ability to translate UI/UX designs and wireframes into high fidelity user interfaces
• Proven experience applying domain driven design to build complex business applications
• In-depth knowledge of relational and columnar SQL databases, including database design
• Experience in REST and/or GraphQL
• Comfort with Agile operating models (practical experience of Scrum / Kanban)
• General knowledge of business processes, data flows and the quantitative models that generate or consume data
• Excellent communications skills and the ability to work with subject matter experts to extract critical business concepts
• Independent thinker, willing to engage, challenge or learn
• Ability to stay commercially focused and to always push for quantifiable commercial impact
• Strong work ethic, a sense of ownership and urgency
• Strong analytical and problem-solving skills
• Establish trusted partnerships with key contacts and users across business and engineering teams

Preferred Qualifications

• Financial Services industry experience
• Experience with Pure/Legend
• Working knowledge of open-source tools such as AWS lambda, Prometheus
• Expertise in data warehousing concepts (e.g. star schema, entitlement implementations, SQL v/s NoSQL modeling, milestoning, indexing, partitioning)
• Deep understanding of multidimensionality of data, data curation and data quality, such as traceability, security, performance latency and correctness across supply and demand processes
• Experience in distributed system design