Lead, Quant Engineer

GLOBAL LEADING ASSET MANAGER WITH A DIVERSE & INCLUSIVE CULTURE As the Global Asset Management business of Prudential, we’re always looking for ways to improve financial services. We’re passionate about making a meaningful impact - touching the lives of millions and solving financial challenges in an ever-changing world. We also believe talent is key to achieving our vision and are intentional about building a culture on respect and collaboration.

When you join PGIM, you’ll unlock a motivating and impactful career – all while growing your skills and advancing your profession at one of the world’s leading global asset managers! If you’re not afraid to think differently and challenge the status quo, come and be a part of a dedicated team that’s investing in your future by shaping tomorrow today.

At PGIM, You Can!

As a Quant Platform Engineer within PGIM Credit Technology, you will build and evolve the platforms, tooling, and data infrastructure that support the Quantitative Modelling and Strategies (QMS) organization. Working closely with quantitative researchers, technology teams, and data specialists, you will develop scalable platforms, services, and data infrastructure that enable quant teams to build and operate investment analytics. This role combines strong Python engineering, data engineering, and distributed computing expertise with close partnership across both quant and technology organizations.

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.

This role is ideal for an engineer who enjoys building platforms, data infrastructure, and developer tooling that enable quantitative research and investment analytics. The successful candidate will work at the intersection of technology and quantitative research, helping QMS teams build and operate analytics more effectively.

Bachelor's or higher degree in Computer Science. Significant experience building and delivering enterprise-scale software, analytics, and data platforms. Deep expertise in Python software development. Significant experience in data engineering, distributed computing and large-scale data processing. Experience building quantitative analytics, risk management, portfolio management, investment research, or quant platforms. Experience partnering closely with quantitative researchers, investment teams, and technology organizations. Understanding of fixed income, credit, asset management, or broader financial markets.

Strong analytical, problem-solving, and communication skills, with a collaborative mindset and focus on delivering business impact.

Experience with distributed computing and data processing frameworks such as Ray, Dask, Apache Spark, Apache Beam, or similar technologies. Experience with event-driven architectures and messaging platforms such as Kafka, RabbitMQ, or similar technologies. Experience with modern software engineering practices including monorepos, CI/CD, automated testing, and Python developer tooling.

* PGIM welcomes all applicants, even if you don't meet every requirement. If your skills align with the role, we encourage you to apply.

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