A data engineer will use Snowflake, SQL, Airflow, and AWS (S3, Lambda) to support a UK leading banking client with data warehousing and workflow management.

Design, build, and maintain data pipelines using Python, SQL, Spark, and AWS. You will join Aquent's client, a financial technology company, working against a critical engagement to ensure data integrity across international operations.

Work on large-scale data projects for a public-facing critical national infrastructure organisation. Modern data engineering practices and technologies are required; no specific tools are listed in the posting.

Build and maintain data pipelines and platforms using Python, SQL, and cloud services (AWS/GCP), often with Airflow and Spark. You will work on critical commercial and operational data platforms that process transactional, revenue, and user performance data to drive business decisions.

You'll build production data pipelines using Apache Spark (PySpark), Databricks, Delta Lake, and SQL, with Unity Catalog, CI/CD, Terraform, MLflow, Kafka, and cloud platforms like AWS/Azure/GCP. Unifeye is a Databricks-first consultancy delivering Lakehouse data platforms for enterprise clients. No team size is stated.

MUFG★3.3 (1k)· London

Senior AI engineer in MUFG's Global Markets Engineering Office; role builds AI solutions using generative AI, agentic workflows, RAG, prompt orchestration, workflow automation, and data-driven decision-support tools. The position identifies, designs, and embeds AI solutions to improve productivity, control effectiveness, and operational resilience within a specific business product line.

Databricks★3.0 (21)· London

Lead a team of pre-sales Solutions Architects using the Databricks Data + AI Platform, Big Data, AI, and cloud technologies. The team drives adoption of the platform in the UK&I Retail and Consumer Packaged Goods sectors, supporting complex sales cycles and partner go-to-market strategies.

Goldman Sachs★3.9 (2.3k)· London

Design, implement, and maintain quantitative models and risk frameworks using C++, Java, or Python for Goldman Sachs' Corporate Treasury division, which manages the firm’s liquidity, funding, balance sheet and capital to maximize net interest income.

Python, SQL, AWS, IaC (Pulumi or Terraform), and likely Airflow, dbt, Spark, Kafka. You will build ETL/ELT pipelines ingesting and normalising data from fragmented legacy police systems for AI-powered investigation software and smart hardware. This is a founding role on a 7-person engineering team.

Macquarie Group★3.8 (315)· London

This global technical leadership role uses AWS and/or Google Cloud, LLMs, agentic systems, tool-calling, and workflow orchestration to design and deploy AI solutions at enterprise scale. The role sits within Commodities and Global Markets, which helps clients manage financial and commodity market risks, access capital, and trade physical commodities. The position has global scope, spanning business enablement, application design, and intelligent automation across the group.

WPP Media★4.0 (1)· London

Lead a multi-faceted Engineering and BI team designing data pipelines using Adverity, dbt, and SQL within an AWS-native environment (Amazon S3, Redshift). The role governs solution architecture for OpenDoor, WPP’s partnership with Amazon, delivering large-scale digital transformation and advertising data infrastructure for a top global client.

Lead the design and architecture of cloud-native, distributed systems, APIs, and data platforms powering Fasanara Open Quant, a quantitative multi-strategy multi-manager hedge fund. Build core investment, portfolio, risk, and data technology while working directly with portfolio managers, quantitative researchers, and traders.

Ares Management★3.3 (33)· London

This senior full-stack engineer works with cloud-native architectures, microservices, Kubernetes, messaging/event streaming, APIs, and CI/CD. They build scalable applications, data services, and platform capabilities across Ares' global credit investment lifecycle, including deal origination, underwriting, portfolio monitoring, risk management, and analytics.

BlackRock★3.8 (632)· London

This role involves building full-stack features using Python, .NET, React, and TypeScript, along with APIs, microservices, and SQL Server, MongoDB, or Snowflake. You’ll join Preqin’s London Engineering team, part of BlackRock, developing cloud-native SaaS solutions for its private markets data platform. The position covers end-to-end product development, CI/CD, and production support.

Work with Python, modern AI platforms, LLMs, APIs, distributed systems, MCPs, and tool-use frameworks to build AI-powered applications, assistants, and agentic workflows. You will drive AI adoption across QRT’s High Frequency Trading business, creating tools that improve productivity in research, development, and trading operations.

You will design and implement data pipelines and ETL processes using Microsoft Azure tools (Data Factory, Azure Synapse, Azure Databricks), PostgreSQL, T-SQL, and Python with Pandas and PySpark. Your team builds cutting-edge Agentic solutions for internal and global customer use, curating datasets and maintaining the data lake.

You'll work with NVIDIA's AI stack: TensorRT-LLM, Triton, RAPIDS, NIM, NeMo, AgentIQ, and Azure AI services, plus Python, Docker, and Kubernetes. You'll design, prototype, and deliver secure, scalable NVIDIA-enabled AI proofs of concept, accelerators, and production solutions for enterprise and public-sector clients.

You'll build and deploy AI agents using Microsoft Copilot Studio and integrate with enterprise data platforms like Microsoft Fabric. This role is with a large UK transport and infrastructure organisation, focusing on delivering business-facing AI agents and automation to improve decision-making and productivity.

Wise★3.5 (42)· London

You’ll build and maintain label integrity for Risk ML models using Python or Java, SQL, ML frameworks (neural networks, NLP, Transformers/LSTMs, GNNs, SVM), data pipelines, and Kafka. Joining Wise’s Risk ML and Intelligence team, you’ll own label quality, statistical monitoring, audit design, and end-to-end model training/deployment at the global money-movement company.

Work with Python, PyTorch, generative models, and cloud infrastructure for ML deployment and optimisation. Join an AI research company developing generative models for scientific discovery, deploying and fine-tuning them for customers.

You'll build production AI applications using Python, OpenAI/Claude LLMs, RAG architectures, and Google Cloud (Vertex AI, BigQuery, Cloud Run), plus Docker and CI/CD. The work involves copilots, document processing, and conversational platforms for Brown & Brown UK, one of Europe's largest insurance groups.

Build GenAI applications with LLMs and orchestration frameworks using production-grade Python on Azure and Databricks. Apply CI/CD, containerisation, and MLOps to take ML systems from ideation to production for a UK consumer services company’s 15-person central AI function.

You’ll work with Azure AI Foundry, Copilot Studio, Databricks Mosaic AI, MLflow, LangChain, LangGraph, AutoGen, Python, SQL, Scala and Azure OpenAI. The role focuses on building and deploying production-ready GenAI, RAG and Agentic AI prototypes and workflows for commercial teams in Trading & Supply.

You will design, build and deploy AI solutions using Python, LLMs, Generative AI and Agentic AI frameworks, alongside MLOps, LLMOps, CI/CD and containerisation on Azure. You’ll join a central AI Centre of Excellence delivering production-ready machine learning, predictive and automation use cases. This role helps establish AI engineering standards and governance.

Interns will use Python, R, and bioinformatics libraries (NumPy, pandas, scikit-learn, PyTorch, Biopython) to develop computational workflows and apply AI/ML to genomics, drug discovery, and other biological areas. The team at Lyna works on real-world biological problems at the intersection of AI and computational science.