Core Quantitative Platform Engineer (C++/Python) in London

Core Quantitative Platform Engineer (C++/Python) in London

London Full-Time 60000 - 80000 Β£ / year (est.) No working from home possible
Deutsche Bank

At a Glance

  • Tasks: Join the GSA team to enhance the Kannon platform using C++ and Python.
  • Company: Deutsche Bank, a leading global bank with a focus on innovation.
  • Benefits: Competitive salary, health benefits, and opportunities for professional growth.
  • Other info: Collaborative environment with exposure to trading desks and quants.
  • Why this job: Make an impact in finance by developing high-performance software solutions.
  • Qualifications: Experience in C++/Python and a passion for quantitative analytics.

The predicted salary is between 60000 - 80000 Β£ per year.

Deutsche Bank is seeking a Core Quantitative Strategic Analytics Developer in London. The role joins the Group Strategic Analytics (GSA) team to extend the Kannon platform, primarily in C++ and Python, delivering cross-asset QP/L, risk and pricing solutions while enabling DevOps and automated controls.

You will work with trading desks, quants and engineers across groups to design and implement high-performance core functionality, with a focus on scalable, robust software and modern CI/CD.

Core Quantitative Platform Engineer (C++/Python) in London employer: Deutsche Bank

Deutsche Bank is an excellent employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. With a strong focus on employee growth, the company provides extensive training opportunities and a hybrid working model that promotes work-life balance, alongside competitive salaries and flexible benefits such as a non-contributory pension and generous holiday leave.

Deutsche Bank

Contact Details:

Deutsche Bank Recruitment Team

We think you need these skills to ace Core Quantitative Platform Engineer (C++/Python) in London

Python
SQL
Data Engineering
Problem-Solving Skills
Communication Skills
ETL/ELT Processes
Data Pipeline Development