Hybrid London Quant Platform Engineer (Python/Data)

Prudential Financial; Greater London; Hybrid; GBP 90.000 - 140.000; Vollzeit

Benefits dieser Stelle

Private Medical Insurance

Annual Leave 25–28 days

Retirement Savings Plan

Life Assurance & Income Protection

Zusammenfassung

PGIM Credit Technology in London is seeking a Quant Platform Engineer to build and evolve platforms, data infrastructure, and services that empower the QMS organization to develop and operate investment analytics.

You will work closely with quantitative researchers and technology teams, delivering Python-based tooling, scalable data platforms, and distributed computing capabilities that drive performance and business impact.

Qualifikationen

• Bachelor's or higher in Computer Science.
• Experience delivering software, analytics, and data platforms.
• Expertise in Python software development.
• Experience in distributed computing and large-scale data processing.
• Experience partnering with quantitative researchers and investment teams.

Aufgaben

• Design and develop platform capabilities, services, and tooling using Python.
• Build and support data platforms, quantitative libraries, distributed computing infrastructure, and shared services used by QMS researchers and investment teams.
• Partner closely with quantitative researchers and technology teams to align platform capabilities with business needs.
• Contribute to architecture, code reviews, testing, performance optimization, and operational excellence.
• Drive continuous improvement through automation, innovation, and engineering best practices.

Kenntnisse

Python

Data engineering

Distributed computing

Communication

Analytical thinking

Ausbildung

Bachelor's in Computer Science

Tools

Ray

Dask

Apache Spark

Apache Beam

Kafka

Jobbeschreibung

PGIM Credit Technology in London is seeking a Quant Platform Engineer to build and evolve platforms, data infrastructure, and services that empower the QMS organization to develop and operate investment analytics.

You will work closely with quantitative researchers and technology teams, delivering Python-based tooling, scalable data platforms, and distributed computing capabilities that drive performance and business impact.