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.

This role involves working with Python, PyTorch, JAX, CUDA, Linux, Docker, Kubernetes, Slurm, Ray, Flyte, and Argo. The team builds ML and physics-based infrastructure for drug discovery, including simulation workflows and agent-usable scientific pipelines. Engineers improve code quality, GPU efficiency, and distributed execution while making research tools scalable and maintainable.

Use Python, SQL, graph databases, Docker, Kubernetes, and LLMs to own Kharon’s risk-propagation engine that evaluates entities in a knowledge graph and surfaces risk signals. The role spans research, data engineering, and product to evolve a production system for global security analytics.

Lead a team of Data Scientists and ML Engineers building AI solutions for financial markets using LLMs, Generative AI, Deep Learning, Transformers, Agentic AI, Python, PyTorch, TensorFlow, Hugging Face, LangChain, Semantic Kernel, Azure AI Foundry, AWS AI Services, and MLOps/LLMOps practices.

You will build AI agents using Python, SQL, Docker, Kubernetes, AWS (RDS, EKS, S3), GitHub Actions, RAG pipelines, BM25, vector search, hybrid retrieval, and knowledge graphs. These agents interpret geopolitical and financial signals for Kharon, a company providing global security risk intelligence.

Deloitte★3.9 (14k)· London

Design, build and deploy intelligent agents and automations using Microsoft Copilot Studio, Power Automate, Power Apps, Dataverse and Microsoft 365. You will work within Deloitte Tax & Legal’s Digital team to create production-ready, low-code solutions that improve efficiency and quality in professional services delivery.

Work with Python, LLMs, RAG pipelines, vector databases, Hugging Face Transformers, LangChain, PyTorch, and Docker to build production AI systems. Design, develop, and deploy AI-powered solutions such as conversational AI, document intelligence, and backend services for the Global Analytics team.

Python, FastAPI, Docker, DuckDB (nice-to-have), JSON Schema, Git, and RESTful APIs. You will design and ship ETL pipelines that transform raw bank data into the FIRE regulatory reporting standard. Suade is a regtech SaaS company automating compliance and risk solutions for financial institutions.

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 will work with Microsoft Fabric, Azure Data Services, Power BI, and Medallion architecture to design and build a cloud-based Lakehouse platform. This role leads a major data transformation for a renowned cultural organisation, creating scalable pipelines and semantic layers. You will manage and mentor a small team of data engineers.

Work with Excel, SQL, Python, R, Tableau, Power BI, and Azure AI Fundamentals. Newto Training provides a data analytics career programme with live instructor-led training, project work, and exam preparation for entry-level roles.

Work with Python, FastAPI, Docker, DuckDB, JSON Schema and Git to design, build and ship client ETL pipelines that map raw bank data onto the FIRE regulatory reporting standard. You will maintain a shared ETL framework, write validated mapping code, and mentor junior engineers at Suade, a regtech SaaS company automating compliance for financial institutions.

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.

Senior Data Engineer at Softwire, a UK digital consultancy, working with Python, SQL, Databricks, Snowflake, Fabric, and AWS/Azure/GCP across data architecture, pipeline design, and governance. You'll lead complex data engineering projects for clients across public and private sectors—from healthcare research platforms to energy market infrastructure—while mentoring junior engineers and shaping technical direction on multi-stakeholder engagements.

You'll design and own end-to-end RAG pipelines for payments domain content using Python, Azure Data Factory, Functions, ADLS, CosmosDB, and AI Search, with CI/CD via GitHub Actions and Azure DevOps. RedCompass Labs builds AI-powered payment transformation and financial crime detection solutions, including the RedFlag Accelerator for identifying human trafficking. You'll collaborate with AI engineers and payments experts to turn regulatory documents and handbooks into a reliable retrieval layer for their proprietary multi-agent AI platform.

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.

Work with Microsoft Fabric, Databricks, Azure, Snowflake, Python, Spark, SQL/NoSQL, PowerShell, Azure Data Factory and Azure DevOps to build a Fabric Data Lakehouse for USS’s Investment Management business, implementing scalable ETL/ELT frameworks across a medallion architecture. Share knowledge across a small team of data engineers and collaborate with architects, business stakeholders and data teams.

Work with Microsoft Azure data platforms: Azure Synapse, Azure SQL Server, Azure Data Factory, Azure DevOps, Microsoft Fabric, and OneLake; also uses DBT and Spark. You will modernize core data platforms—ingesting data from MS Dynamics CRM, Finance & Operations, and SAP SuccessFactors—to power analytics, AI-driven insights, and executive decision-making.

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.

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.

You'll build distributed backend services and microservices using Java (Spring/Spring Boot), Python, messaging frameworks like Kafka/MQ, and Unix/Linux, with CI/CD and containerization. The Role sits on the Risk Services team within Global Markets, designing scalable systems for risk data processing, analytics, and reporting workflows.