Top Data Engineer Jobs in London

Develop and deliver a scalable data pipeline using Azure Databricks for transforming data into standardized datasets, focusing on automation and CI/CD integration.

As a Data Engineer, you will design and build data pipelines, models, and infrastructure for analytics and machine learning while ensuring data quality and compliance.

Design, build, and optimise scalable data pipelines and Lakehouse layers (Bronze/Silver/Gold) in Microsoft Fabric using SQL and PySpark. Integrate ERP/CRM/APIs, ensure data quality/governance, support Power BI semantic models, monitor and troubleshoot pipelines, and collaborate with stakeholders for analytics and reporting.

Lead the development and architecture of new data services and products around clinical insights, focusing on data analysis and reporting.

As a Senior Data Platform Engineer, you will design and operate a scalable data platform, support analytics, mentor junior engineers, and drive technical excellence.

As a Lead Data Engineer, you will design and develop software for data processing, lead a team, ensure quality, and manage technical proposals.

The role involves building ETL pipelines, optimizing datasets, leveraging public cloud technologies, and integrating with data science initiatives to support business-critical data and analytics products.

The role involves building, scaling, and operating a validated data platform for clinical data, ensuring data integrity, and mentoring team members.

The Senior Data Engineer will design and implement data pipelines for fraud prevention, collaborate with teams, and ensure high quality code while participating in agile methodologies.

Responsible for designing and maintaining data pipelines, collaborating with teams for data quality, and developing engineering solutions using various tools and technologies.

As a Data Engineer, you will build and maintain data systems for drug safety AI tools, ensuring reliable data processing and storage for research teams.

The Data Engineer will design and maintain the data infrastructure, develop data warehousing solutions, automate data pipelines, and ensure compliance with governance policies.

Build and maintain a near real-time financial dashboard by integrating market and forecast APIs, automating financial models, and crafting clear visual narratives using Flourish and Canva. Collaborate with design and marketing partners, ensure data accuracy and performance, and optimize data flows across multiple feeds.

Lead design and evolution of scalable real-time and batch ETL pipelines and data platform. Own performance, reliability, and data quality; drive architecture and tooling choices; collaborate with product and backend teams; mentor engineers and shape target architecture to support trader-facing analytics and low-latency data needs.

Design, build and operate large-scale data ingestion, processing and distribution infrastructure. Lead architecture and technical design for real-time messaging, distributed storage, data processing and analytics workloads. Mentor engineers, enforce high engineering standards, and translate business requirements into scalable production systems.

Design, build, and operate resilient ETL/ELT pipelines ingesting data from Azure SQL, SaaS, and event streams into BigQuery. Implement declarative pipelines (DLT), support low-latency ML feature pipelines, ensure operational health, monitoring, and incident response. Collaborate with analytics and AI/ML teams, mentor junior engineers, optimise platform performance, and influence platform architecture and tooling decisions.

As a Senior Data Engineer, you will design and develop large-scale data processing solutions and lead technical components in agile teams.

The role involves leading the Data Platform, designing scalable pipelines, enhancing data quality, collaborating with AI teams, and mentoring engineers.

The Data Engineer will build and maintain data pipelines, ensuring quality and performance while collaborating with teams to support platform evolution and product delivery.

As a Data Engineer, you will create data pipelines, design data models, and enable self-service analytics, improving data accessibility and insights.

The Tech Lead will mentor the team, translate research needs into solutions, design cloud systems, and implement DevOps practices.

The Senior Machine Learning Engineer will design and build data pipelines for multimodal training, ensuring quality and efficiency in data handling. Responsibilities include collaborating with scientists, maintaining infrastructure, and implementing validation frameworks for reliable ML workflows.

The Senior Software Engineer will lead the Core Data team to improve APIs, systems, and data pipelines, focusing on backend engineering and team mentoring.

The Senior Data Engineer will deliver complex data engineering for insights and analytics, collaborating with multiple stakeholders and managing team outputs.

The Data Reliability Engineer will enhance the resilience and scalability of data infrastructure, focusing on automation and reliability. Responsibilities include managing data pipelines, operating Kubernetes clusters, and defining observability standards.