Quantitative Engineering

Goldman Sachs

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
New York, NY
Salary
$150,000–$225,000 / yr
Posted
75 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $169k
This role $188k
$119k most similar roles pay here $236k

This role pays more than 64% of similar roles. Most pay $130,500–$206,875 — the shaded band above. At the midpoint, this role pays about $188k versus about $169k for comparable roles.

Based on 240 similar postings.

Employer

About Goldman Sachs

Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.

Goldman Sachs currently has 134 open roles on FindRole.

Listed pay typically runs $137,000–$250,000 across 55 roles with salary data.

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At a glance

TL;DR · Quantitative Engineering

The GBM, Public, ETF One Delta Strat - Quantitative Engineering role is situated within the ETF Trading Desk in the One Delta Equity group. This developer-heavy seat focuses on managing the technical infrastructure for systematic trading, pricing frameworks, and daily fund reconciliation across equity ETFs. The engineer will be responsible for operational engineering to resolve bottlenecks, providing real-time troubleshooting for production systems, and designing high-performance data stacks for a systematic block market-making business. Key responsibilities include translating quantitative pricing models into production-grade code and optimizing the JSI layer for low-latency communication between Java infrastructure and the proprietary Slang environment. Candidates must possess expert proficiency in Java and Python, along with skills in Git, CI/CD, and performance profiling. The role addresses technical challenges in ETF market microstructure, delta-one products, and systematic hedging strategies.

What you'll do

  • Identify and resolve technical bottlenecks in the trading lifecycle through automated solutions.
  • Provide real-time troubleshooting for production trading systems to ensure high availability during market volatility.
  • Design, build, and maintain the high-performance technology and data stack for systematic block market-making.
  • Translate quantitative pricing models and business logic into production-grade code for risk management.
  • Develop and optimize the JSI layer for low-latency communication between Java infrastructure and proprietary Slang environments.
  • Build and maintain large-scale ETL processes and time-series data pipelines.

What we're looking for

  • Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related technical field.
  • Expert-level proficiency in Java and Python to write clean, scalable, and testable code.
  • Strong foundation in CS fundamentals including data structures, algorithms, and systems design.
  • Experience or strong interest in working with proprietary languages and cross-language integration (JSI).
  • Deep understanding of software engineering lifecycles, including CI/CD, version control (Git), and performance profiling.
  • Exceptional debugging skills for complex, distributed systems under time-sensitive conditions.
  • Prior experience in a systematic trading group, HFT firm, or "Strat" team at a major investment bank (preferred).
  • Experience with ETL processes, time-series data pipelines, or proprietary financial languages like Slang (preferred).

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