You'll work with Python (Pandas, Arrow, Spark) and potentially Lakehouse tools (Delta Lake, Databricks, AWS). Joining Global Data Engineering, you provide first-line support for a high-frequency trading market maker, ensuring robust data pipelines and APIs for trading teams.

You will work with Python, LLMs, agentic workflows, retrieval-augmented generation (RAG), and internal AI platforms. The Tactical AI Automations team deploys and supports AI tools across PIMCO's Portfolio Management and Analytics groups, including operational support for Lane Assist and POET (portfolio optimization tools).

The Specialist Works★4.8 (5)· London

You will primarily work with Python, SQL, Azure, and the Adverity platform to create, monitor, and optimize data pipelines. You will be a key member of a dynamic media activation team, delivering bespoke marketing intelligence reports and ETL solutions for the agency's clients.

JPMorgan★3.9 (20k)· London

You will work with Python, AWS, EKS, Docker, Kubernetes, Kafka, and MLOps tools. As a member of the Applied AI/ML Software Engineering team within CIB Security Services Technology, you will build cloud-based frameworks for hosting machine learning models alongside Data Scientists to integrate AIML solutions into production systems.

Bloomberg★3.8 (1.1k)· London

You will work with Python, SQL, PySpark, Pandas, NumPy, Airflow, dbt, Kafka, Iceberg, Trino, Superset, and data visualization tools. The Entity Data team manages core entity data for over 7 million public and private companies, supporting reference data and private markets; as Data Quality Manager you define and execute the quality strategy.

Capgemini★3.7 (11k)· London

Design, build, and manage data pipelines and models using AWS Snowflake, Azure Data Lake, Databricks, Redshift, and BigQuery. Automate CI/CD with Azure DevOps, GitHub Actions, Jenkins, GitLab CI/CD, and provision infrastructure with AWS CloudFormation, Docker, ECS, EKS, and Kubernetes. Capgemini is an AI-powered global business and technology transformation partner.

Work with Python, Pandas, NumPy, Scikit-learn, SQL, LLMs, RAG, and MLOps to design, build, and deploy enterprise-scale AI/ML solutions improving operational efficiency, service resilience, and customer outcomes at LSEG, a global financial markets infrastructure and data business.

Hays★3.5 (1.4k)· London

You will work with Snowflake, AWS, Python, SQL, dbt, Airflow and GitLab CI/CD. The role is part of a major cloud transformation programme building a next-generation, cloud-native data platform, including ETL/ELT pipelines and migrating legacy environments.

LSEG★3.7 (402)· London

You will use Python (Pandas, NumPy, Scikit-learn), SQL, cloud-based MLOps platforms, and Generative AI/LLM/RAG tools to build predictive models and AI solutions that improve operational efficiency, service resilience, and customer outcomes for LSEG's financial markets infrastructure.

You will design, build, and operate AWS infrastructure, engineer Kubernetes environments (EKS, Docker, Helm), and use Terraform for infrastructure-as-code. You will support critical investment and trading systems, improve CI/CD pipelines with GitHub Actions and GitOps (Argo CD), and work with databases like Snowflake, Aurora, and SQL Server. You will take end-to-end ownership of production systems, solve complex problems across distributed environments, and influence cloud architecture and reliability standards.

Wise★3.5 (42)· London

Build backend

Use Python, Pytest, SQL, Azure, Microsoft Fabric, Cosmos DB, and GitLab/GitHub to design and execute manual and automated tests. You'll validate data pipelines, transaction flows, and reporting within a large-scale financial services transformation programme using Agile and CI/CD practices.

Apple★4.1 (14k)· London

You'll work with Go, Python, Linux, and distributed systems including object stores, databases, and data pipelines on private/hybrid cloud. The team builds and operates the data platform infrastructure behind Apple’s services (iCloud, iTunes, Siri, Maps), keeping petabyte-scale workloads reliable and performant.

Automat-it★0.0· London

You will work with AWS data services (S3, Glue, Redshift, Kinesis, MSK, EMR, Athena, Lambda, IAM) and modern tooling like Iceberg, dbt, Kubernetes, Docker, Terraform, and CI/CD. As a Senior Data Architect, you design and deliver end-to-end production-grade data platforms on AWS directly for startup customers. Automat-it is an AWS Premier Partner and Managed Services Provider.

Goldman Sachs★3.9 (2.3k)· London

You will work on backend micro-service development using Java, Spring, and MongoDB. At Goldman Sachs, a global investment banking and securities firm, you’ll build scalable software, low-latency systems, and data-driven solutions for trading, sales, and asset management.

Design, develop, and optimize data pipelines using SQL, Python, Scala, Java, or Spark, along with ETL/ELT tools like Azure Data Factory, AWS Glue, and Apache Airflow, on cloud platforms such as Azure, AWS, or GCP. You will work with databases (SQL Server, Snowflake, MongoDB), big data technologies (Spark, Kafka, Databricks), and orchestration tools to build scalable cloud-based data platforms supporting enterprise analytics and machine learning.

Work with XGBoost, Random Forests, LSTM, transformers, LLMs, Python, R, SQL, Azure, Git, PowerBI, and Looker. You will drive business outcomes by applying AI/ML to solve problems in NLP, computer vision, and recommender systems for a global academic publisher.

Sage★3.5 (901)· London

You will apply Python, R, SQL, XGBoost, Random Forests, LSTM, transformers, and Azure services to solve problems in NLP, computer vision, and recommender systems. The team builds AI/ML models to drive commercial impact for Sage, a global academic publisher of books, journals, and library resources.

You will use Python, R, SQL, Git-based platforms, Azure services, PowerBI, and Looker to build AI/ML solutions—including NLP, Computer Vision, recommender systems, and LLMs—for a global academic publisher of books, journals, and library resources.

You'll work with Python, FastAPI/Flask/Django, PostgreSQL/MySQL, Databricks, Azure cloud infrastructure, and CI/CD tools to build data pipelines and APIs for Breathe's battery management platform. The Platform & AI team processes time-series battery test data, automates analysis with AI, and provides infrastructure supporting R&D, product development, and service delivery across the company's physics-based battery management software used by major automotive and electronics brands.

Design, deploy and optimise machine learning models and LLM solutions using Azure Databricks, Azure ML, Azure AI Foundry, LangChain, LangGraph and Python. You will build production AI/ML infrastructure and agentic AI workflows for a global law firm, enhancing legal processes through innovative technologies. MLflow, PyTorch, Docker, and Kubernetes are also used.

Lead Cloud Engineer role: work with Terraform, Kubernetes, Amazon Bedrock, AWS, and Infrastructure as Code; architect AI-native infrastructure including Vector Databases, RAG architectures, and production-grade Agentic Workflows. The role is with an AI-native consulting partner, delivering cloud, AI, and platform engineering projects for clients such as PayPal and adidas. You will guide and mentor a team of cloud engineers.

The Senior Data Practice Lead works with SQL, Python, data modelling, transformation architecture, pipeline design, data testing, observability, CI/CD, and data governance. At YLD, a software consultancy embedding engineers in client teams, this role builds the data practice through hands-on delivery, client engagement, and mentoring. Reports to Head of Engineering.

Multi-cloud platform engineer (senior/lead) for Defaqto, working with AWS, Azure, Google Cloud, Terraform/OpenTofu, Pulumi, Ansible, Docker, Kubernetes, Python, Go, GitOps, CI/CD, BigQuery and AI/LLM tooling. Builds and operates the company’s hybrid-cloud internal developer platform and self-service golden paths for human engineers and AI agents.

You will work with Java, Azure, Databricks, GitLab CI/CD, JUnit, Cucumber, and REST APIs. You will build scalable automation frameworks, test data pipelines, and support CI/CD integration for enterprise-grade cloud-native applications in banking or financial services.