Data Engineer - Systematic Trading Team - £250k+

Data Engineer – Systematic Trading Team – £250k+

Data Engineer – Systematic Trading Team – £250k+

Paragon Alpha – Hedge Fund Talent Business provided pay range

This range is provided by Paragon Alpha – Hedge Fund Talent Business. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

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Paragon are searching for Data Engineer to join the front office team at a top-tier systematic hedge fund. This isn’t a back-office role—you’ll be working side-by-side with quants, traders, and researchers, making sure the right data is delivered to the revenue generators.

Scope:

• Building and scaling ETL pipelines that can handle market data feeds across multiple asset classes (equities, crypto, FX, fixed income)
• Working directly with the people using the data: quants, portfolio managers, and risk teams.
• Making sure things don’t break (and if they do, you know how to trace and fix it) with modern observability tools (grafana, datadog, new relic)
• Constantly improving performance, resilience, and data quality

.

What we’re looking for:

• Solid experience with market data engineering in a trading/hedge fund/bank environment.
• Strong Python and SQL skills (bonus if you’ve dabbled in distributed systems or cloud infra).
• Someone who knows ETL inside-out and can deal with messy, high-volume real-time feeds.
• Curiosity, problem-solving mindset, and the ability to talk to quants without needing a translator.
• Strong data structures/algorithms
• Proven experience working in cloud native environments (AWS)

Recent placements in this team have come from big tech, hedge funds and start ups. We need someone who can iterate rapidly and deal with a fast changing ecosystem.

Please apply if you want to leverage your data/engineering skills in a systematic hedge fund at the top of their game.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Finance

• Industries

  Data Infrastructure and Analytics

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