Quantitative Developer

Radley James; New York (NY); On-site; USD 400,000 - 750,000; Full time

Job summary

A prominent financial services firm is hiring a Data Quant Engineer for its New York office. This role focuses on developing robust systems for processing large-scale financial data and optimizing access for trading models. Successful candidates will possess strong programming skills and experience in data engineering within the financial context.

Qualifications

• Strong experience with Python for data processing.
• Solid experience with SQL and various data storage systems.
• Familiarity with cloud infrastructure and distributed systems is a plus.

Responsibilities

• Design and build scalable data pipelines for financial data.
• Collaborate with researchers to transform data into alpha signals.
• Implement quality checks and data lineage tracking.

Skills

Python programming

Data processing and analysis

SQL

Problem-solving

Education

Bachelor’s, Master’s, or PhD in Computer Science, Math, Physics, Statistics

Tools

PostgreSQL

KDB+

ClickHouse

AWS

Kubernetes

Airflow

Job description

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This range is provided by Radley James. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$400,000.00/yr - $750,000.00/yr

As a Data Quant Engineer, you’ll sit at the intersection of quantitative research, data engineering, and software development. Your focus will be on designing and implementing robust systems for acquiring, processing, and analyzing large-scale financial data that powers the research and trading models.

Key Responsibilities:

• Design and build scalable data pipelines for ingesting and curating structured and unstructured financial data (e.g., tick data, fundamental data, alternative datasets).
• Collaborate with quants and researchers to transform data into usable alpha signals.
• Develop tools to validate, clean, normalize, and enrich diverse datasets.
• Optimize access to historical and real-time data for backtesting and live trading.
• Implement quality checks, monitoring, and data lineage tracking to ensure data reliability and transparency.
• Support research environments with high-throughput computing and fast access to time-series data.

Required Qualifications:

• Bachelor’s, Master’s, or PhD in Computer Science, Math, Physics, Statistics, or related field.
• Strong Python programming skills, particularly for data processing and analysis (Pandas, NumPy, etc.).
• Solid experience with SQL and data storage systems (e.g., PostgreSQL, KDB+, ClickHouse).
• Understanding of market data formats, time series handling, and real-time data processing.
• Familiarity with distributed systems, cloud infrastructure, and compute clusters (e.g., AWS, Kubernetes, Airflow) is a strong plus.
• Exposure to quantitative research, financial data, or trading systems is highly desirable.
• Excellent problem-solving ability, attention to detail, and ability to work collaboratively with technical and non-technical stakeholder.

Seniority level

• Seniority level

  Not Applicable

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Finance

• Industries

  Capital Markets, Financial Services, and Investment Management

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