Job Description

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.

Leveraging our own Legend offering, our engineers build efficient data solutions that source, curate, and distribute critical data to our businesses, including financial product, pricing, transaction, and client reference data. Our engineers collaborate closely with the business to design and curate business-specific data models, and to transform and distribute data for optimal storage and retrieval.

We are a leading enterprise leveraging data to drive business decisions and innovation. Our team solves complex problems and creates scalable solutions that enhance our data infrastructure. We need a talented and motivated hands-on Software Engineer who will help us in our mission to transform data into actionable insights. 

You are a Software Engineer who has strong, hands-on programming skills and want to solve complex problems; you will use these skills to help us build and optimize data systems that deliver insights. Your abilities will help us design, develop, and maintain our data infrastructure. You will collaborate with cross-functional teams across firm divisions to ensure that our data infrastructure is pleasant, robust, safe, efficient, and scalable. You are driven to Get Things Done.

Here are some of our current projects:

1/ Build a consolidated data platform and infrastructure in the cloud for data analytics, data science, AI/ML: the multi-cloud, cloud-native Lakehouse 

2/ Implement features like dynamic Data Lineage, Data Reproducibility, and a consolidated Data API Serving Stack into our open-source Legend data platform 

3/ Ensure the Legend data platform (https://github.com/finos/legend) works seamlessly across Python, Slang (the firm’s homegrown language for pricing/risk), and Java.

4/ Solve hard problems around language bindings, integrations, C/C++/JVM and technologies like Apache Arrow, Iceberg etc.

5/ Build easy-to-use end-to-end data engineering workflows on the data platform for experimentation/research/AI training in the cloud 

Technical Skill Requirements:

• Strong programming skills in language(s) such as Python, Java, or Scala.
• Proficiency in SQL and background in relational databases (e.g., PostgreSQL, MySQL, SingleStore).
• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services.
• Knowledge of data warehousing solutions (e.g., Snowflake, BigQuery, Redshift).
• Fluency with version control systems (e.g., Git) and CI/CD pipelines.
• Experience with ETL tools and data processing frameworks, when to use them and when not to.
• Understanding of data modeling, data architecture, and data governance principles.
• Ability to think on your feet, be pragmatic, labor for simplicity, and collaboratively solve for the problem.
• Communicate and convey complex technical concepts to both technical and non-technical stakeholders.

Preferred Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

Why Join Us:

• Make a difference by seeing your work impact the business.
• Work with talented collaborators in an inclusive work environment that values diversity and innovation.
• Continually learn and be able to develop yourself professionally.
• Be rewarded with a competitive salary and comprehensive benefits package.

   

ABOUT GOLDMAN SACHS

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. 

We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers. 

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

© The Goldman Sachs Group, Inc., 2023. All rights reserved.

Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity

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