Front Office Python Engineer: Trading Analytics & Backtesting

Susquehanna International Group, LLP

Lower Merion Township (Montgomery County)

On-site

USD 140,000 - 230,000

Full time

14 days+

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Job summary

Susquehanna International Group, LLP is seeking a Front Office Python Engineer to build trader-facing applications that empower data analysis, visualization, and decision-making across trading desks.

The role blends data engineering with application development and quantitative tooling, focusing on backtesting, analytics, and real-time trading workflows. Collaboration with traders, quants, and technologists will turn data into scalable tools and insights.

Qualifications

  • 3+ years of professional experience building Python applications or data systems.
  • Strong Python skills, including experience with Pandas and NumPy.
  • Experience with backend frameworks such as Flask or FastAPI.
  • Experience with data pipelines and structured/unstructured datasets, APIs, real-time data feeds, SQL, and databases.
  • Familiarity with data visualization tools and event-driven architectures.

Responsibilities

  • Research, design, and develop systems used in backtesting and data analysis.
  • Build Python-based applications and tools for tactical analytics in trading decisions.
  • Monitor strategy performance and diagnostics.
  • Develop ad-hoc tools and systematic data solutions.
  • Improve trading workflows and optimize performance.
  • Design and maintain data pipelines and datasets for research and trading.
  • Refine systems based on desk feedback and evolving strategies.

Skills

Python
Pandas
NumPy
APIs
SQL
Data visualization
Event-driven

Tools

Flask
FastAPI

Job description

Susquehanna International Group, LLP is seeking a Front Office Python Engineer to build trader-facing applications that empower data analysis, visualization, and decision-making across trading desks.

The role blends data engineering with application development and quantitative tooling, focusing on backtesting, analytics, and real-time trading workflows. Collaboration with traders, quants, and technologists will turn data into scalable tools and insights.

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