Real-Time Data Engineer — Trading Platform (NY)

Experis Technology Group; New York (NY); In loco; USD 120.000 - 180.000; Tempo pieno

Vantaggi offerti da questo lavoro

Medical and Prescription Drug Plans

Dental Plan

Vision Plan

Health Savings Account

Health Flexible Spending Account

Dependent Care Flexible Spending Asset

Supplemental Life Insurance

Short Term and Long Term Disability

Business Travel Insurance

401(k), Plus Match

Weekly Pay

Descrizione del lavoro

Experis Technology Group is seeking a Data Engineer in New York to support an operational and data pipeline stack for a high-performance algorithmic environment. You will help ensure the data stack is robust, scalable, and reliable so production systems perform at their best when it matters most.

Responsibilities include building automated solutions to reduce bottlenecks, providing real-time troubleshooting for production trading systems, and translating complex pricing models into

Competenze

• Expert-level proficiency in Python, Spark, and SQL.
• Strong CS fundamentals: data structures, algorithms, systems design.
• Experience with CI/CD, Git, and performance profiling.
• Ability to design scalable, production-ready data pipelines.

Mansioni

• Handle operational aspects of the algorithm stack, ensuring robustness, scalability, and high performance.
• Identify and resolve bottlenecks across the trading lifecycle by building automated solutions.
• Provide real-time, expert-level troubleshooting for production trading systems, 24/7 availability.
• Design, build, and maintain the data stack powering systematic block marketmaking logic.
• Translate quantitative pricing models and business logic into production-grade code for real-time pricing and risk management.

Conoscenze

Python

Spark

SQL

Strumenti

CI/CD tooling

Git

Performance profiling

Descrizione del lavoro

Experis Technology Group is seeking a Data Engineer in New York to support an operational and data pipeline stack for a high-performance algorithmic environment. You will help ensure the data stack is robust, scalable, and reliable so production systems perform at their best when it matters most.

Responsibilities include building automated solutions to reduce bottlenecks, providing real-time troubleshooting for production trading systems, and translating complex pricing models into