Top Data Engineer Jobs in London

Design, implement, and maintain market data feed handlers, optimize system performance, and collaborate with traders and engineers to ensure data integrity.

The role involves creating and managing data assets, building data pipelines, ensuring data quality, and providing technical leadership for product teams.

The Senior Data Engineer will design and build scalable data systems, manage data pipelines, and collaborate with cross-functional teams to ensure data quality, performance, and observability in a fast-paced environment.

Design and develop data processing modules and reporting systems, optimize data pipelines, and work with teams to ensure data quality and governance.

Design and implement real-time market data systems, drive technical innovation, provide leadership, and optimize processing workflows.

The Data Engineer will maintain the data stack, optimize reporting systems, and support business needs through efficient data management. Responsibilities include data modelling, managing ETL processes, and ensuring high-quality data availability.

As a Data Engineer at Depop, you'll drive impactful data initiatives, shape data foundations, and deliver reliable data pipelines to support marketing teams.

The Data Engineer will design and enhance data platforms, build data solutions, support data integrity, and collaborate with internal stakeholders in an Agile environment.

As a Data Engineer at Starling, you will build cloud-native data warehouses and ML platforms, improving tooling within AWS and GCP.

The Data Engineer role involves managing data pipelines, ETL tasks, database administration, and supporting analytics by ensuring data accuracy and reliability across cloud and on-premises environments.

Join a team to design and build scalable data pipelines on GCP for financial institutions, ensuring governance and compliance while collaborating on data solutions.

Design and build cloud-based data pipelines using AWS tools, collaborate with clients, ensure data governance, and mentor junior engineers.

The Data Engineer will manage the data lifecycle, integrate data sources, design ETL processes, develop data models, and create dashboards, while ensuring data quality and compliance.

As a Senior Software Engineer, you'll build a full-stack platform for subscription apps, optimize data pipelines, and lead technical projects.

The AI Data Engineer designs and builds scalable data pipelines, integrates AI services, and ensures data readiness for advanced analytics across Convatec's Azure ecosystem, collaborating with AI Engineers and Data Scientists.

Design, build, and optimize data pipelines for analysis and machine learning. Collaborate on data infrastructure, ensure data quality, and support model deployment.

The Data Engineer will build and maintain data pipelines, architecture, and CI/CD infrastructure, collaborate with stakeholders, and support AI components to enhance data management capabilities.

The Data Engineer will enhance data architecture, support data pipelines, and collaborate with business users, ensuring data quality and efficient processes.

The Python Data Engineer will develop AI applications, manage data processing, mentor team members, and ensure code quality while collaborating with different teams.

Design, develop, and maintain data pipelines using Kafka; build infrastructure with Terraform; troubleshoot data engineering issues and collaborate with teams.

The Data Engineer will design, develop, and maintain data pipelines and platforms, ensuring reliability and supporting data science initiatives while leading technical improvements.

The Credit Data Engineer will build and maintain data infrastructure for credit decision-making and portfolio performance, ensuring data quality and enabling analytics for the credit function.

As a Data Engineer at UBDS, you will build data pipelines and solutions, collaborate in teams, and contribute to data-driven decision-making.

The Data Engineer will develop cloud-based data pipelines, manage integrations, create data services, and ensure data quality using various modern tools and programming languages.

The role involves designing, developing, and maintaining scalable distributed systems for data delivery, analytical databases, and data retrieval processes. Responsibilities include optimizing performance, collaborating with teams, and enhancing customer-facing APIs.