Our client is a leader in quantitative trading, leveraging cutting-edge technology and petabyte-scale data to drive global high frequency trading strategies. We’re seeking an experienced Front Office Python Developer with a passion for large-scale data engineering to enhance their proprietary trading platform.

This role sits at the intersection of trading, data infrastructure, and quantitative research. You’ll work directly with traders, quants, and other developers to build scalable data pipelines, integrate structured/unstructured datasets, and optimize high-performance querying systems—all while shaping the future of our real-time trading infrastructure.

Key Responsibilities

Own and optimize large-scale data pipelines (petabyte-scale data lakes) feeding into trading strategies.

Design and implement high-performance ETL workflows, integrating diverse data sources (market data, alternative datasets, unstructured feeds).

Collaborate with quants and traders to translate research concepts into efficient, scalable data solutions.

Develop tooling for real-time data validation, monitoring, and visualization to ensure data integrity.

Enhance our proprietary data platform using modern open-source technologies (e.g., distributed compute, cloud-native services, containers, streaming frameworks).

Solve complex data challenges—low-latency processing, schema design for time-series data, and optimizing queries across massive datasets.

Ideal Candidate

You’re a Python-focused developer with front office experience, passionate about solving data problems at scale. You thrive in a fast-paced trading environment and want to work on systems where performance and accuracy directly impact P&L.

Must-Have Qualifications

Strong Python (production-level, with expertise in data libraries like Pandas, NumPy, PySpark, or Dask).

Experience with large-scale data systems (SQL/NoSQL databases, distributed processing, or cloud data platforms).

Proven ability to own data pipelines end-to-end—from ingestion to analytics-ready outputs.

Familiarity with modern data stack tools (e.g., Airflow, Kafka, Kubernetes, Iceberg/Databricks, or similar).

Understanding of financial markets/trading data (tick data, order books, reference data).

Strong collaboration skills—able to work with quants, traders, and infra teams.

Nice-to-Have

Experience with real-time data systems (stream processing, WebSocket APIs).

Knowledge of quantitative finance concepts (alpha research, signal generation).

Background in performance optimization (query tuning, parallelization, caching).

Exposure to CI/CD, DevOps practices, or infrastructure-as-code.

Why Join?

Work on one of the most advanced trading platforms in the industry, handling billions in daily volume.

Direct impact on trading strategies—your code and data solutions drive real-time decisions.

Collaborate with top-tier engineers, quants, and traders in a meritocratic, tech-driven culture.

Above-market compensation, cutting-edge tech stack, and a flat, high-performance team structure.

If you’re a data-savvy Python developer excited by the challenge of building systems at the forefront of quantitative trading, please apply!