Quant Developer and Trading Engineer Careers

Quant Developer and Trading Engineer

Quant developers and trading engineers build the systems that research, price and trade. Learn the main roles, technical skills, interviews and how to prepare.

Intermediate3 min readUpdated 3 Oct 2026

Lesson 28 of 44

Behind every modern trading firm is software: systems that receive market data, run strategies, send orders, manage risk, store data and support research. Quant developers and trading engineers build and maintain those systems. Some work close to researchers, turning prototypes into production code and building research platforms. Others focus on low latency infrastructure, where microseconds matter. As trading has become almost entirely electronic, these engineers have become as central to many firms as the traders themselves.

Types of roles#

Role	Focus	Typical languages
Quant developer	Production implementation of models, pricing libraries, research tools	Python, C++
Low latency engineer	Market data handlers, order gateways, matching of speed critical paths	C++, Rust, sometimes FPGA languages
Trading platform engineer	Order management, risk systems, user interfaces	Java, C#, C++, Python
Data engineer	Market data pipelines, storage, research datasets	Python, SQL, Spark
Infrastructure and SRE	Servers, networks, deployment, monitoring	Linux, scripting, cloud tools
Hardware engineer	FPGAs and network hardware	Verilog, VHDL

Key technical skills#

Skill	Lesson
Strong programming and data structures	Python for Trading
Systems programming and performance	CPU Affinity, NUMA and Cache Optimization and Lock-Free Programming and Ring Buffers
Networking	Networking for Traders
Market data and protocols	Feed Handlers and Normalization and FIX Protocol
Databases and storage	Data Storage, Compression and Caching
Testing and reliability	Market Data Replay and Alerts, Error Handling and Reconnection
Linux	Linux for Traders

Understanding the trading domain, such as order types, market structure and risk, makes engineers far more effective. See Order Types Explained and Market Structure Basics.

What the work looks like#

Interviews#

Coding: algorithms and data structures, often in C++ or Python.
Systems design: designing an order book, market data system or matching engine. See Matching Engines.
Low level knowledge: memory, caches, concurrency, networking for latency roles.
Debugging and code review exercises.
Some probability and trading questions at many firms.

How it differs from big tech engineering#

	Trading firm engineering	Typical big tech engineering
Users	Traders and researchers in the same firm	Millions of external users
Feedback	Direct and immediate, often measured in P&L	Product metrics over time
Performance focus	Latency and correctness are critical	Scale and availability
Cost of bugs	Can be immediate financial losses	Usually user impact and outages

See Risk Controls and Kill Switches for why correctness matters so much.

Preparing for the role#

Master a language deeply, especially C++ for low latency or Python for research tooling.
Build trading related projects: an order book, a backtester, a market data recorder. See Order Book Feeds: Snapshots and Incremental Updates and Building Trading Bots.
Learn Linux and networking fundamentals.
Study market structure to understand what the systems do.
Practise systems design questions.

Frequently asked questions#

What does a quant developer do?#

Builds and maintains the software used for research, pricing, trading and risk at trading firms, often turning researchers' models into production code.

Is C++ required for trading firms?#

For low latency roles, usually yes; many other roles use Python, Java or other languages.

How is a quant developer different from a quant researcher?#

Developers focus on building reliable, fast software systems; researchers focus on finding signals and building models, though the roles overlap.

Next, learn about running portfolios in Portfolio Manager.

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