Senior Python Developer

Senior Python Engineer – Systematic Trading & Market Data

The Client

A leading quantitative investment firm is hiring a Senior Python Engineer to help scale the data platform powering systematic research and trading across global markets.

This is a front-office engineering role focused on building high-performance data infrastructure used directly by quant researchers and trading teams.

The Role

The successful candidate will work on large-scale market data systems, real-time pipelines, cloud-native infrastructure, and research tooling that supports alpha generation across systematic equities strategies.

What you’ll build:

• Real-time and historical market data platforms
• Python-based APIs and data services for quant research
• Scalable time-series storage and retrieval systems
• Streaming and event-driven data architecture
• Distributed compute and research infrastructure
• Cloud-native tooling and platform automation

Tech environment:

Python | AWS | Kafka | Kubernetes | Docker | Airflow | SQL | Linux | Time-Series Data | Distributed Systems

Depending on experience, you may also work with:

Spark, Dask, Redshift, Snowflake, KDB, OneTick, Prometheus, Grafana, CI/CD tooling, and low-latency data workflows.

What they’re looking for:

• Strong Python engineering experience in production environments
• Experience building scalable backend or data-intensive systems
• Strong understanding of system design, performance, and architecture
• Experience working with cloud infrastructure and modern engineering tooling
• Solid SQL and data engineering fundamentals
• Linux and automation/scripting experience
• Ability to work closely with technical stakeholders in fast-moving environments

Previous experience in systematic trading, hedge funds, electronic trading, market data, or quantitative research environments is highly beneficial. Strong engineers from adjacent high-scale environments are also encouraged to apply.

Why this role stands out:

• Direct impact on trading and research outcomes
• Highly technical engineering culture
• Greenfield platform and scaling challenges
• Close collaboration with quant researchers and portfolio teams
• Strong compensation and long-term growth potential
• Opportunity to work on genuinely complex distributed data problems

Ideal backgrounds may include:

Systematic Hedge Funds | HFT | Prop Trading | Investment Banking | Market Data Platforms | Big Tech Infrastructure | Large-Scale Data Engineering