Quant Platform Engineer - Python

McCabe & Barton; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

A leading global investment management firm in London is hiring a Quant Platform Engineer to join a growing Quantitative Technology team. This role sits at the intersection of quantitative research, software engineering, data engineering, and platform development, working with teams across London and New York.

You will modernise and expand the firm's quantitative research platform, evolve existing capabilities, and contribute to long-term technology strategy.

Qualifications

• Experience building data platforms, analytics platforms or research infrastructure.
• Exposure to financial markets, including asset management, banking, hedge funds, trading, commodities, equities or fixed income.
• Experience working with large-scale data environments and modern data engineering technologies.
• Distributed systems, event-driven architectures, low-latency platforms or system-to-system communication frameworks.
• Excellent collaboration and stakeholder management skills.
• Quant Development or Quant Platform Engineering backgrounds.
• Experience working directly with quantitative researchers.
• Spark, Apache Beam, Snowflake or similar large-scale data technologies.

Responsibilities

• Developing and enhancing Python-based research and analytics platforms.
• Building scalable infrastructure used by quantitative researchers and investment professionals.
• Designing and supporting large-scale data processing and engineering solutions.
• Partnering closely with quant researchers, technology teams and stakeholders across London and New York.
• Driving platform modernisation, automation and engineering best practice.
• Taking increasing ownership of a strategically important platform over time.

Skills

Data platforms

Analytics platforms

Big data platforms

Distributed systems

Stakeholder mgmt

Quant research

Python

Platform modernization

Low latency

Research collaboration

Tools

Spark

Apache Beam

Snowflake

Python

Job description

A leading global investment management firm is looking to hire a Quant Platform Engineer to join a growing Quantitative Technology team in London. This is a newly created position offering the opportunity to work directly with quantitative researchers and help shape the future of a business-critical research and analytics platform.

This role sits at the intersection of quantitative research, software engineering, data engineering, and platform development. You'll join a highly collaborative team spanning London and New York, building technology that directly supports investment decision-making and quantitative research.

The Role

As the primary software engineer embedded within the London Quant team, you will play a key role in modernising and expanding the firm's quantitative research platform. Rather than building from scratch, you'll help evolve existing capabilities, introduce modern engineering practices, and contribute to the long-term technology strategy of an expanding quantitative investment function.

Key responsibilities include:

• Developing and enhancing Python-based research and analytics platforms.
• Building scalable infrastructure used by quantitative researchers and investment professionals.
• Designing and supporting large-scale data processing and engineering solutions.
• Partnering closely with quant researchers, technology teams and stakeholders across London and New York.
• Driving platform modernisation, automation and engineering best practice.
• Taking increasing ownership of a strategically important platform over time.

What We’re Looking For

We're seeking strong engineers with a passion for building platforms and solving complex data challenges.

• Experience building data platforms, analytics platforms or research infrastructure.
• Exposure to financial markets, including asset management, banking, hedge funds, trading, commodities, equities or fixed income.
• Experience working with large-scale data environments and modern data engineering technologies.
• Distributed systems, event-driven architectures, low-latency platforms or system-to-system communication frameworks.
• Excellent collaboration and stakeholder management skills.
• Quant Development or Quant Platform Engineering backgrounds.
• Experience working directly with quantitative researchers.
• Spark, Apache Beam, Snowflake or similar large-scale data technologies.

Ideal Candidate

This opportunity is particularly well suited to someone who wants to move closer to the investment decision-making process while retaining a strong engineering focus. The successful individual will have a desire to build, own and continually improve platforms rather than operate solely within project-based delivery environments.