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.

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.

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 on Python (or comparable language) with multiple programming languages, Unix systems, and database technologies. Partner with trading, research, and data teams to develop core analytics, build data analytics trading tools, and integrate data into models for the Commodities team of a market-leading global hedge fund.

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.

SmartestEnergy★4.1 (15)· London

You will work with Microsoft Azure Data Platform, Microsoft Fabric, PySpark, SQL, Python, Azure DevOps, CI/CD, and Power BI to build enterprise-scale data pipelines and Data Lakehouse/Data Warehouse solutions. The team develops modern cloud-based data solutions supporting ETL/ELT processes across Medallion Architecture for SmartestEnergy’s energy digitisation and decarbonisation goals.

Deloitte★3.9 (14k)· London

You will design and continuously improve Next-Gen Detection and Response capabilities, working with SIEM/SOAR (Google SecOps), EDR/XDR (Crowdstrike, Microsoft Defender XDR), and NDR (Corelight) tools across hyperscaler environments. You bridge security strategy with technical blueprints, developing HLD/LLD documents within Agile, DevOps, or Kanban delivery models and using TOGAF. The role sits in Deloitte’s Cyber practice, solving clients’ toughest cyber security challenges.

HCLTech★3.7 (11k)· London

Work with Quantexa Decision Intelligence Platform, Spark/PySpark, Python/Scala, and Big Data (Hive/HDFS) to design and develop data ingestion, transformation, and ETL pipelines. Focus on entity resolution, network analytics, and graph-based data models for analytics use cases.

AXA★3.9 (2.9k)· London

Design and implement secure architectures for enterprise security and AI/ML initiatives across AXA, using Docker, Kubernetes, cloud security, API security, micro-services, MLOps/MLSecOps platforms, threat modeling, and SSDLC. Defines technical security standards and reference architectures aligning with frameworks like NIST AI RMF and ISO/IEC 42001. Reports to the Chief Security Officer.

bp★3.8 (5.2k)· London

Work hands-on with Python, SQL, C#, Spark/PySpark, Palantir Foundry, planlogic EOS ETRM, Stonebranch, and AWS to build and maintain backend services, RESTful APIs, front-end components, and data pipelines. You will support bp’s LNG Energy Trading and Risk Management applications, including bespoke solutions for trade capture, operations, analytics, risk, reporting, and finance. This Staff Engineer role also includes mentoring and line management of the engineering team.

You'll build scalable data infrastructure for AI applications using Python, SQL, Spark, dbt, LangChain, and cloud platforms (AWS, Azure, GCP), working with data pipelines, embeddings, vector search, and LLMOps tools like Terraform and LangSmith. QuantumBlack, McKinsey's AI division, develops next-generation AI systems and enterprise solutions for clients across industries. You'll collaborate with Data Scientists and ML Engineers in cross-functional Agile teams based in London, supporting the firm's AI adoption and complex problem-solving at scale.

Design and develop solutions on the Quantexa Decision Intelligence Platform, building data ingestion and ETL pipelines with Spark/PySpark, and using Python/Scala. The role involves entity resolution, network analytics, graph-based data models, and integrating structured/unstructured data, working with the Big Data ecosystem (Hive/HDFS).

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.

T. Rowe Price★3.6 (709)· London

SQL, Excel, Jupyter notebooks, Jira, and Confluence are used. The role partners with the Fixed Income Investments technology team to build next-generation cloud-first portfolio management capabilities for front office engineering teams.

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.

Bloomberg★3.8 (1.1k)· London

You'll work with Python, SQL, and modern AI-assisted tools to own the data management strategy and roadmap for Bloomberg's environmental regulatory data products, including EU Taxonomy, SFDR, and CSRD. You'll partner with Engineering and Product to evolve data models, quality frameworks, and operational controls that ensure scalable, auditable data products.

Mastercard★4.0 (846)· London

You will work with LLMs, GenAI, Agentic AI, PowerBI, Qlik Sense, Tableau, AWS, Databricks, and Microsoft Azure, with Python and SQL preferred. Within Vocalink’s Data & Insights function, you will deliver data-led and AI-driven solutions for UK payment reporting and customized analytics.

Capgemini★3.7 (11k)· London

Manage large-scale data programmes using cloud platforms, ETL/ELT, Power BI, Tableau, and Agile SAFe. The role focuses on insurance data management across policy, claims, underwriting, and customer domains, including integration with Guidewire and Duck Creek. You will lead cross-functional teams of data engineers, architects, and analysts.

MAREX★3.2 (6)· London

Design and implement resilient data ingestion, orchestration, and provisioning using APIs, event streaming, CI/CD, and infrastructure-as-code for Marex's enterprise data products. This role supports the firm's global financial services platform by delivering trusted, reusable data assets and integration capabilities for operational, regulatory, and analytical use cases.

Build and ship AI features using LLMs, retrieval-augmented generation (RAG), and Python or .NET, deploying on Azure. You will join Shawbrook’s AI Engineering squad to move AI from proof-of-concept into production-grade systems supporting lending, deposits, operations, risk, and customer experience.

Design, build, and deploy LLM/RAG pipelines, agentic workflows, and backend APIs in Python on Azure. You will drive production-grade AI for lending, deposits, risk, and customer experience at Shawbrook Bank. Mentor other engineers in the AI Engineering squad.

You will lead a small cross-functional data pod building data pipelines, models and services in Python, SQL and Snowflake to turn supply chain data into customer-facing sustainability insights. The role combines hands-on data engineering with technical leadership and line management of the pod's engineers.

You will work with Python, PyTorch, PyTorch Lightning, TensorFlow, and experiment tracking tools to design and implement custom machine learning model components for Search, Retrieval, Ranking, or Content AI. You will join the Tripadvisor Experiences R&D Team, which is evolving the marketplace for travel experiences by powering how millions of users discover and plan itineraries. You will act as a technical lead and pod architect, and mentor mid-level and associate ML scientists.

Design, build, and deploy quantitative models using Python, R, and libraries (numpy, pandas, scikit, pytorch, tidyverse, caret, ggplot) plus NLP tools, SQL, AWS, Sagemaker, DataBricks, Snowflake, MLFlow, and Weights & Biases. The team creates systematic country risk analytics and ML/NLP pipelines for BMI’s market insights, supporting clients in risk assessment.

Deloitte★3.9 (14k)· London

You will work with SQL, Python, R, and cloud technologies to design end-to-end AI and data solution architectures. As part of Deloitte’s AI & Data Strategy, Governance and Architecture team, you help clients build data-driven programmes that transform their organisations.