Quant jobs / Deutsche Bank

Quantitative Trading Engineer (Java)

A lead engineering role in the quantitative fixed-income engineering team, building the software behind rates and credit trading strategies. It sits between desk quants and the platform engineering group.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Add features to trading strategies and the shared trading stack
Profile and fix stability or performance problems in e-trading services
Review code and pair with engineers across regions
Agree changes with desk quants and traders and ship them to production
Reuse and improve common components from the core platform team

What they ask for

Required

Strong Java
High-performance or low-latency application development
E-trading system development
Production delivery track record
Computer engineering fundamentals

Preferred

Python 3
KDB
Continuous delivery practices
Technical degree

Education: Technical degree preferred
Experience: Experienced lead engineer with a record of delivering e-trading systems
Languages and tools: Java
Python
KDB+/q
Markets: fixed-income, credit

How to prepare

Write a low-latency Java order-handling or pricing service and profile its GC and latency behaviour
Learn concurrency patterns and lock-free structures in Java
Study how a quote-to-trade pipeline works in an e-trading system
Practise basic kdb+/q alongside Python for tick data analysis

What to study

The HFT Quant Developer roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on Deutsche Bank’s site before applying: requirements, location and pay can change after we check them.

View the posting on Deutsche Bank’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Deutsche Bank and doesn’t handle applications.