Real-Time Data Engineer – Trading & Market Data

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

Job summary

Mondrian Alpha is seeking a Data Engineer to design, build, and maintain scalable data pipelines that ingest market, trade, and reference data for researchers and traders. You will own data quality, latency SLAs, and be part of a fast-moving environment that values timely, accurate information.

You will collaborate with quant researchers and traders to translate data needs into robust engineering solutions, ensuring reliability of production data systems and exploring new data sources as

Qualifications

• 3+ years of data engineering experience in a production environment.
• Strong Python and SQL.
• Experience with large-scale or time-series data systems.
• Direct experience with market or financial data; non-negotiable for the role.
• Comfort working in a fast-moving, low-latency environment.

Responsibilities

• Design, build, and maintain data pipelines that ingest and normalize market, trade, and reference data at scale.
• Own data quality and latency SLAs for pipelines feeding quant research and live trading systems.
• Build and maintain time-series and event-driven data infrastructure supporting backtesting and production strategies.
• Partner directly with quant researchers and traders to understand data requirements and translate them into engineering specs.
• Monitor, troubleshoot, and improve reliability of production data systems.
• Evaluate and integrate new data sources as research needs evolve.

Skills

Python

SQL

Time-series data

Market/financial data

Low-latency environment

Data pipelines

Tools

Kafka

AWS

GCP

kdb+/Q

Job description

Mondrian Alpha is seeking a Data Engineer to design, build, and maintain scalable data pipelines that ingest market, trade, and reference data for researchers and traders. You will own data quality, latency SLAs, and be part of a fast-moving environment that values timely, accurate information.

You will collaborate with quant researchers and traders to translate data needs into robust engineering solutions, ensuring reliability of production data systems and exploring new data sources as