GSET Reference Data Engineer
Goldman Sachs
Job Overview
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Job Description
GSET Reference Data Engineer at Goldman Sachs
At Goldman Sachs, we connect people, capital, and ideas to help solve problems for our clients. We are a leading global financial services firm providing investment banking, securities, and investment management services to a substantial and diversified client base that includes corporations, financial institutions, governments, and individuals.
Our Impact
Goldman Sachs Electronic Trading (GSET) strives to be the top provider in electronic trading by building superior technology and delivering high quality products through investment in people, platforms, and products. Join the team and participate in the development and launch of best-in-class products for top clients across the industry. We are looking for eager, nimble, and ambitious engineers to join our growing team of visionaries, driving GSET to achieve and exceed its goals.
Your Impact
The GSET Platform team builds the core services and components of our electronic trading platform for clients and trading desks. This ranges from positions management and resource distribution to client workflow management and controls. Our low latency platform is built with speed, reliability, and resiliency in mind, where every microsecond counts, and uptime is critical. We work directly with our traders and product development teams to build new functionality for clients, adapt the platform to meet regulatory and industry changes, and expand into new markets.
As a member of the team, you will play an integral role on the trading floor. This is a dynamic, entrepreneurial team with a passion for technology and the markets, with individuals who thrive in a fast-paced changing environment. You should be willing to participate in the full product lifecycle from requirements gathering, design, implementation, testing, support, and monitoring.
Responsibilities
- Design, build and maintain high-performance, high-availability, high-capacity, yet nimble and adaptive Java based reference data platforms.
- Work in partnership with the wider engineering and product teams to design and implement best-in-class solutions.
- Work closely with our global counterparts to ensure we’re building features and systems that can be reused and leverage work and experience from other regions.
Skills & Experience We’re Looking For
BASIC SKILLS & QUALIFICATIONS
- Strong Java programming skills with database experience.
- Excellent academic record in a relevant technical field, e.g., Computer Science and Engineering.
- High desire to produce organized, readable, tested, and maintainable software.
- Ability to balance multiple, time-sensitive projects while maintaining a longer-term, strategic focus.
- Effective communicator in both written and verbal mediums.
Beneficial Skills & Qualifications
- Prior experience working on reference data platforms for electronic trading.
- Knowledge of Kafka, SQL, and/or Linux.
- Prior experience designing and implementing distributed systems modeling complex workflows.
- Prior experience in the financial industry.
- Understanding of common data structures and optimizations regarding memory and runtime performance.
Key skills/competency
- Java
- Reference Data
- Electronic Trading
- Distributed Systems
- Kafka
- SQL
- Linux
- Low Latency
- Financial Services
- Data Structures
How to Get Hired at Goldman Sachs
- Research Goldman Sachs' culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your GSET Reference Data Engineer resume: Highlight Java, database, distributed systems, and financial market expertise.
- Network strategically: Connect with current Goldman Sachs employees, especially in GSET or similar tech roles, on platforms like LinkedIn.
- Prepare for technical interviews: Expect rigorous questions on Java, data structures, algorithms, system design, and database concepts, with a focus on low latency.
- Demonstrate passion for finance and technology: Showcase your understanding of electronic trading, market dynamics, and how technology drives financial services.
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