Quant Engineer: Data, Backtesting & Low-Latency (NY)

Digital Waffle; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Digital Waffle in New York is seeking a Quant Engineer for a role that blends engineering and research. You will build data pipelines, backtesting frameworks and production systems to run quantitative strategies, while staying close to modelling to iterate quickly on ideas.

This is a 5-days-a-week in-office position in NYC. The role combines performance-sensitive data work with collaboration on model implementation, feature engineering and productionisation, delivering robust data and live

Qualifications

• Strong Python production experience with Pandas, NumPy, Polars.
• Solid SQL fundamentals for data pipelines.
• Experience with performance-sensitive engineering (C++, Rust, or optimized Python).
• Track record building data, backtesting or execution infrastructure.
• Experience with time-series data issues (survivorship bias, lookahead, data gaps).
• Familiar with AI engineering tools to raise output.
• High autonomy and pragmatic decision-making.
• Willing to be in-office 5 days a week in New York.

Responsibilities

• Build and maintain high-performance data pipelines in Python and SQL.
• Design backtesting infrastructure and simulation environments.
• Develop low-latency execution and signal-processing systems.
• Collaborate with researchers on model implementation and productionisation.
• Own data quality, timing and reproducibility across lifecycle.
• Work with storage/compute tools (DuckDB, kdb+, Parquet-based lakes).
• Leverage AI tooling to accelerate workflows.

Skills

Python prod experience

Pandas

NumPy

Polars

SQL fundamentals

Performance engineering

C++/Rust

Time-series data

AI tools

Autonomy

In-person collaboration

Tools

DuckDB

kdb+

Parquet

Job description

Digital Waffle in New York is seeking a Quant Engineer for a role that blends engineering and research. You will build data pipelines, backtesting frameworks and production systems to run quantitative strategies, while staying close to modelling to iterate quickly on ideas.

This is a 5-days-a-week in-office position in NYC. The role combines performance-sensitive data work with collaboration on model implementation, feature engineering and productionisation, delivering robust data and live