Use Python, Azure, Docker, Kubernetes, Apache Airflow, and GitHub Actions to build scalable ETL pipelines, financial data pipelines, and cloud-native infrastructure. This front-office role is at a systematic equity hedge fund modernising its quantitative research platform, working directly with portfolio managers and researchers. Experience with S&P Xpressfeed, Snowflake, Bloomberg, MSCI Barra, Databricks, and LLMs is advantageous.

Rebuild data infrastructure for a market-neutral systematic equities fund using Python, Microsoft Azure, Docker, Azure Kubernetes, Apache Airflow, and GitHub Actions for CI/CD. Work on ETL pipelines, vendor integration, and cloud-based research platforms, with relevant experience in Snowflake, Bloomberg, MSCI Barra, or Databricks. The role spans data engineering and quantitative development to transform financial data into investment signals.

Use Python, Azure, Docker, Kubernetes, Apache Airflow, and GitHub Actions to modernize a systematic equity hedge fund’s quantitative research and engineering platform. You will build scalable ETL pipelines, cloud-native infrastructure, and research-ready datasets, working directly with portfolio managers and quantitative researchers.

Senior KDB developer working with kdb+, q, time-series databases, Unix/Linux, and scripting; also complementary tools like Python, cloud platforms (AWS/Azure/GCP), and AI development tools (GitHub Copilot, Claude). The role designs enterprise-scale kdb+ architectures and builds real-time/historical market-data solutions for a financial technology firm focused on market data and analytics platforms.

Use Core Java, Spring, Linux, relational databases, and multi-threading to build and maintain front office eTrading applications for Fixed Income and Derivatives flows. You will work directly with traders, sales, and quants in a globally distributed team, optimizing performance and supporting low-latency solutions.

You will design and build Python services and APIs using AWS (Lambda, S3, ECS/EKS, Step Functions, Aurora), Kafka, and PostgreSQL/SQL Server/Snowflake to support portfolio construction, trading, and analytics. This Investment Technology role turns research tools into production-grade platforms for Portfolio Managers and Quantitative Researchers across Equities, Fixed Income, and Alternatives.

Python, Microsoft Azure, Docker, Azure Kubernetes, Apache Airflow, GitHub Actions, Snowflake, Databricks, and OpenAI LLMs. The role rebuilds data infrastructure and transforms financial data into research-ready datasets and signals for a fully systematic market-neutral equity fund.

Core Java, Spring Framework, Linux, and relational databases for low-latency eTrading applications on a globally distributed team building the next generation Front Office Trading System for Fixed Income and Derivatives flows.

Java, Spring Boot, DevOps, and Linux are used to design and develop front office eTrading applications for the trading business, working directly with traders, sales, and quants. The role is part of a globally distributed team.

Jump Trading★3.8 (11)· London

A 10-week internship working with Python on Linux, building and maintaining data pipelines and infrastructure for Jump Trading's proprietary trading platform, using Agile development and production code.

Jump Trading★3.8 (11)· London

You will use advanced TypeScript, Python, and modern Web frameworks to build Web-based applications interacting with Jump Trading’s real-time trading platform. The Core Development team architects and maintains the firm’s world-class trading platform.

Jump Trading★3.8 (11)· London

An FPGA intern on Jump Trading's Core Development team will work with RTL (SystemVerilog/Verilog/VHDL), C, C++, and Python. The team builds next-generation, ultra-low-latency systems using FPGAs to accelerate trading and machine learning algorithms on a global scale.

Jump Trading★3.8 (11)· London

As a core development intern, you will design, code and test the firm's distributed trading system using C++ and Python on Linux, with Git for version control, and gain experience with Agile methodologies. The team builds and maintains Jump Trading's world-class low-latency trading platform and infrastructure.

Invesco★3.9 (499)· London

Senior Engineer works with Python, SQL (PostgreSQL, SQL Server), AWS (Lambda, S3, ECS/EKS, Step Functions, Aurora), Kafka, CI/CD, and AI tools (Copilot, Claude, ChatGPT, Bedrock). The role designs and builds applications and data pipelines for Invesco’s ETF platform, supporting portfolio construction, trading, analytics, and operations across Equities, Fixed Income, and Alternatives.

You will work with Python, TypeScript, AWS (Cognito, Lambda, Fargate, API Gateway, S3, IAM), Terraform, PostgreSQL, and AI tools (Claude, GitHub Copilot, Cursor, LLM APIs). The team builds and evolves scalable microservices for BMLL Lab & Vantage, the company’s SaaS products for data science and visualisation on large financial datasets.

Senior Java engineer working with Java, low-latency, multi-threading, microservices, API design, LLMs, Claude Code, Copilot, MCP, and AI automation. The newly formed Service Modernisation & AI team modernizes critical legacy Java services using AI-driven refactoring and builds AI-powered development tooling.

Visa★3.9 (1.2k)· London

You will work with Java, microservices, Kafka, Kubernetes, MySQL, and event-driven architecture on the FX Client Pricing and Risk team at Visa, building a platform that abstracts foreign exchange complexities behind a simple API for frictionless currency exchange.

Visa★3.9 (1.2k)· London

You'll build and maintain mission-critical foreign exchange trading services—pricing engines, risk management systems, and market data providers—for Currencycloud's API that has processed over 50 billion USD in cross-border transactions. The FX Routing and Aggregation team uses Java 11+, Spring Boot, AWS, Kubernetes, Kafka, and SQL databases to power real-time, high-throughput FX trading microservices handling billions in transactions, with mentoring responsibilities for junior engineers.

Citi★3.9 (21k)· London

You'll lead Java development on Citi's FX risk management platform, architecting high-performance, low-latency systems processing real-time risk data at scale using Java with AI-powered tools including GitHub Copilot, Devin.AI, and Citi Squad integrated into daily workflows, alongside Docker, Kubernetes, and enterprise DevOps pipelines. The team, part of Citi's 30,000-person global technology organization, manages a greenfield application in production for three years with committed long-term investment, delivering weekly releases in an agile environment.