Data Engineer - Proprietary Trading Firm - Up to $500k TC

Saragossa; New York (NY); On-site; USD 450,000 - 550,000; Full time

Job summary

Saragossa is establishing a new quantitative team in New York to build data pipelines that feed into research and live trading decisions. You will work on greenfield development next to traders, handling billions of historical rows, vendor datasets, and entity resolution, with a focus on reliability and scalability.

You come in with strong Python skills and experience with large-scale historical data ingestion, shaping the data infrastructure that directly impacts market actions and research

Qualifications

• Expertise in building and maintaining data pipelines for large-scale historical data.
• Experience ingesting and validating third-party/vendor data feeds.

Responsibilities

• Build greenfield data pipelines powering trading research and live signals.
• Ensure data quality, versioning, and restatements for quantitative workloads.

Tools

Python

Job description

The data you build powers real trading decisions, not dashboards nobody reads.

You are joining one of the world's major quantitative proprietary trading firms, trading every listed product and asset class globally.

This is a greenfield build, a new team, and your fingerprints are on it from day one. Your work sits right next to the money. The pipelines you engineer feed directly into quant researchers finding alpha and developing live trading signals. The loop from your work to research to production trading is short. You feel the impact.

The data problems here are genuinely harder than most environments you have worked in. You are handling billions of historical rows, alternative and vendor datasets, point-in-time correctness, restatements, backfills, and entity resolution.

You are also starting to apply LLMs and agents to unstructured data, so the work keeps evolving.

You are building alongside elite quant researchers and traders. The people around you are operating at the top of the industry, and that shapes how you think and what you build.

You come in with strong Python, no exceptions there. You have worked with large-scale historical data and you know how to ingest and manage third-party and vendor data feeds reliably.

Total compensation reaching up to $500k.

Ready to build something that actually matters in the market?