Senior Data Architect

Radley James; New York (NY); On-site; USD 180,000 - 280,000; Full time

Job summary

Radley James is seeking a Senior Data Architect to lead the design of a next-generation research and simulation data ecosystem. You will architect a unified data platform powering systematic research, backtesting, and alpha generation across global asset classes.

The role requires owning end-to-end data models and collaborating with quants and simulation engineers to define best practices. The candidate should have 7+ years in data architecture or large-scale data engineering, with strong Python

Qualifications

• 7+ years in data architecture or large-scale data engineering.
• Strong Python skills and experience with Parquet, Arrow, Spark, SQL/NoSQL and distributed file systems.
• Expertise in time-series + financial data modeling across multiple vendors and asset classes.
• Experience building data interfaces or APIs for researchers or quantitative analysts.
• Bonus: cloud architectures (AWS/GCP/Azure) and modern data governance.

Responsibilities

• Lead design of the unified data platform powering research, backtesting and alpha generation.
• Collaborate with quants and simulation engineers to define best practices and data models.
• Own end-to-end data architecture across global asset classes.

Skills

Python

Parquet

Arrow

Spark

SQL/NoSQL

Time-series modeling

APIs

Cloud architectures

Job description

A quant hedge fund is seeking a Senior Data Architect to lead the design of their next-generation research and simulation data ecosystem. You will architect the unified data platform that powers systematic research, backtesting, and alpha generation across global asset classes. It is a high-impact role in which you own the end-to-end design of data models and while working closely with quants and simulation engineers and define the best practices.

What They’re Looking For

• 7+ years of experience in data architecture or large-scale data engineering
• Strong Python skills and experience with Parquet, Arrow, Spark, SQL/NoSQL, and distributed file systems.
• Expertise in time-series + financial data modeling across multiple vendors and asset classes.
• Experience building data interfaces or APIs for researchers or quantitative analysts.
• Bonus: experience with cloud architectures (AWS/GCP/Azure) and modern data governance.