You'll work with Microsoft Fabric, PySpark, Python, T-SQL, DAX, Infrastructure as Code, Git, and Azure DevOps. You'll design, build, and maintain data pipelines, lakehouses, and data warehouses within Fabric to drive business intelligence and analytics.

Wise★3.5 (42)· London

You will build scalable systems for business onboarding and verification using Java or JVM languages, Spring framework, JDBC, and relational/non-relational databases with CI/CD pipelines and distributed systems. This engineering team owns end-to-end projects to automate verification, create flexible onboarding journeys, and manage compliance risks for Wise’s money-moving platform across Europe and the UK.

You'll work with Java/JVM and Spring on the backend, React/JavaScript/TypeScript on the frontend, plus CI/CD, distributed systems, and relational/non-relational databases. You'll join Wise's Account Integrity team, building fraud-prevention and financial-crime detection systems to protect customer accounts. Wise is a global technology company for moving and managing money.

Tesco★3.5 (25k)· London

You will work with Java, Spring Boot, Kafka, Apache Flink, Apache Beam, NoSQL databases, Redis, and Apache Camel. The Tesco Personalisation team builds real-time, low-latency services for recommendations, offers, and experimentation across web, mobile, and in-store channels using streaming data and ML.

You'll work with Python, SQL, PySpark, and the PyData stack to build machine learning and analytics solutions for McKinsey's clients across industries, translating business challenges into statistical models and deploying them to production. QuantumBlack, AI by McKinsey is a data science and AI consulting firm applying advanced analytics to solve complex client problems. You'll collaborate with Data Scientists, Engineers, Designers, and Product Managers globally while based in London, with exposure to R&D projects and conference presentations.

Work with Microsoft Fabric (Lakehouses, Warehouses, Dataflows, Pipelines), Azure (SQL, Data Lake, Data Factory), SQL, Python, and REST API/SFTP to build ETL/ELT solutions. You will deliver modern data integration solutions for a diverse portfolio of clients within RSM’s Global VAT Team.

You'll use Java, Kafka, Flink, SingleStore, HDFS/S3, and Scala to build high-performance, low-latency data systems. The Data Platform team in Global Markets owns the post-trade stack, processing high volumes of data and developing an AI-powered analytics UI/agent framework.

Work with Java/Spring, React, JavaScript/TypeScript, CI/CD pipelines, and distributed systems. You'll join the Account Integrity team building a globally scalable fraud prevention engine to protect customer accounts and prevent financial crime using machine learning and real-time monitoring.

You'll use Python, SQL, shell scripting, containerization, infrastructure-as-code tools, and Scala/Java or Python to build and maintain scalable data pipelines. You'll support a financial technology company's data infrastructure, contributing to AI/ML experiences and international applications. No team size is stated.

Cint★3.5 (13)· London

Use Python and SQL for statistical modeling and machine learning to optimize Cint's programmatic research marketplace (Cint Exchange). You will analyze marketplace dynamics, conduct A/B tests, and build predictive models to guide product and pricing strategy.

Hudson River Trading★4.5 (2)· London

You will use Python, C++, Pandas, NumPy, R, or MATLAB to build and maintain predictive trading models. As an algorithm developer, you research and test novel order execution and model training methods, applying

Goldman Sachs★3.9 (2.3k)· London

Build a high-performance, low-latency data platform for post-trade processing using Java, Kafka, Flink, SingleStore, HDFS/S3, and Scala. You will own the full lifecycle of core systems, designing distributed computation and an AI-powered UI/agent framework to deliver intelligent analytics over large-scale business data.

Hudson River Trading★4.5 (2)· London

You will work with Python, Pandas, NumPy, R, and MATLAB to apply statistical analysis and machine learning to vast quantities of market data. The team builds and maintains predictive trading models for the company's high-performance trading infrastructure. You will research, develop, and test order execution methods to increase trading efficiency.

Wise★3.5 (42)· London

You will build and refine financial crime prevention systems using Java (or JVM languages) with Spring, React/JavaScript/TypeScript, and CI/CD pipelines, working 80% backend and 20% frontend. You join the Account Integrity team, which protects Wise’s global platform against fraud via machine learning and real-time transaction monitoring, and you will own projects end-to-end.

Salesforce★4.2 (1.5k)· London

Success Architect works with Agentforce, Data Cloud, Salesforce Clouds, and data platforms like Snowflake, Databricks, AWS. They drive customer success by optimizing technical architecture for data unification and AI-driven automation, enabling personalized engagement and real-time decision-making.

Design, build and optimise ETL data pipelines using Databricks, PySpark, Python, and SQL for a leading global investment bank. You will work on large-scale enterprise data platforms in a fast-paced financial services environment.

You will work with Python, JavaScript, SQL, Kafka, AWS/Azure, PostgreSQL, SQL Server, ClickHouse, and MongoDB. The team designs and delivers real-time, high-performance trading systems for Energy & Commodities, integrating market data, risk, and front-to-back office workflows.

Use Java, Python, Kafka, and RESTful APIs to build cloud-ready, distributed applications with relational/NoSQL databases and caching (e.g., Memcached). You will transform middle-office workflows at PIMCO, a global asset manager, building data infrastructure and reporting to improve investment teams’ access to positions, P&L, and performance data.

Work with Python, DevOps, Linux, Pandas, NumPy, and relational/non-relational databases. You'll join the Vendor Data Group at a global quant firm to build and maintain mission-critical ETL/ELT data integration pipelines and tools for alternative commodity and macro data, collaborating with a trading team.

You will work with AWS, Kubernetes, Terraform, Python, Java or Scala, and AI-driven development tools (Claude, LLMs). You will build and maintain the distributed-compute and data-science platform that powers Macquarie's trading and analytics workflows, collaborating with quantitative analysts and trading desks.

Work with C#, Python, Java, SQL, and AWS (ECS, S3, DynamoDB) to design, build, and maintain TradingHub’s market data environment and analytics. Collaborate with Pricing Quants and Risk Strats to productionise financial markets data for the company’s trade surveillance software.

Develop end-to-end solutions in Python (pandas/numpy) for the Commodities RAD team, building data, research & trading platforms and tools for Portfolio Managers. Also use React/Angular for web frontends and SQL for databases.

Design, build and deploy production Generative AI applications, LLM-powered solutions and agentic frameworks using Python, LangChain, LangGraph, and OpenShift. You will automate enterprise workflows with intelligent agents, working with PostgreSQL and pgvector as part of Citi’s COO-Technology team building scalable AI for global operations. This is an Individual Contributor Staff Engineer role.

Build scalable distributed systems with Java (Spring/Spring Boot) and Python, using Kafka, MQ, XML, and CI/CD in Unix/Linux environments. This Risk Services team within CRISIL supports capital-markets risk data ingestion, processing, analytics, and reporting for Global Markets.

Working with Core Python, Pandas, NumPy, Flask/FastAPI/Django, SQL, and Unix/Linux, you will build backend applications and data processing pipelines for trading and risk management within an investment banking environment, supporting risk calculations, trade workflows, and reporting.