Top Data Engineer Jobs in London

The Lead Data Engineer will design and oversee data pipelines and platforms, ensuring reliability, scalability, and governance while collaborating with various stakeholders.

As a Senior Azure Data Engineer, you'll design and deploy data engineering pipelines using Databricks on Azure, collaborate with clients, and implement best practices in a consulting environment.

Lead architecture and delivery of data solutions on Databricks within Azure, ensuring best practices in data pipeline design and implementation.

The role involves designing and building data pipelines using AWS technologies, leading projects, and mentoring junior engineers in a data engineering context for financial services.

The Principal Data Engineer will design and build scalable data pipelines, collaborate with clients on solutions, and mentor junior engineers in a hybrid environment.

The Senior Software Engineer will scale the Supplier Data Manager for enterprise customers, enhance AI-driven data pipelines, and improve collaboration features while ensuring operational excellence and customer-driven product development.

Build and evolve a high-scale data platform (mondayDB) and end-to-end data applications. Own backend-focused full-stack features, collaborate with product and design, improve architecture, and deliver production-quality user-facing systems.

Build and scale a next-generation data platform (mondayDB 3.0). Design architecture, implement backend-heavy full-stack features, collaborate with product and design, ensure CI/CD delivery, and improve performance and engineering practices for large-scale, user-facing systems.

The role involves designing and maintaining a data platform, enhancing system efficiency, implementing data query solutions, and technical reviews within a data engineering team.

Design, build, and operate highly scalable real-time streaming microservices and data pipelines (Java/Python/Go) using Kafka, Flink/Spark on Kubernetes across multi-cloud and on-prem. Own design, deployment, monitoring, observability, and on-call support while improving platform reliability and developer experience.

Design, build, and maintain scalable ETL/ELT pipelines and an enterprise data warehouse. Manage transformation layers (Dataform/dbt), deploy services with Docker/Kubernetes, implement automated testing, partner with Product and Engineering, mentor peers, and ensure operational reliability for high-frequency energy metering data.

As a Senior Data Science Engineer, you'll lead data science projects, develop algorithms, analyze datasets, and mentor junior team members to enhance trading operations and strategies.

As a Data Engineer, you will build near real-time data solutions by collaborating within an agile team, designing scalable data pipelines, and leveraging AI tools. Responsibilities include maintaining ETL services and developing CI/CD processes.

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.

Build and maintain high-performance pipelines to transform trading and position data into analysis-ready datasets; develop interactive dashboards and web apps (Tableau/self-service tools); support market abuse, policy and supervisory analysis across asset classes; help shape how data is used to monitor and supervise firms and markets.

As a CRM Technology Engineer, you'll enhance data and platform infrastructure for CRM, ensuring reliable customer data handling and effective integrations.

The Data Engineer will develop and scale an operational data platform for energy trading, focusing on real-time analytics, data pipelines, and data services using AWS technologies.

As a Data Engineer, you'll build and optimize data platforms, create data pipelines, and implement ML infrastructure to support business insights and data service needs.

Lead the design and implementation of modern data platforms and pipelines, ensuring high performance and compliance while consulting directly with clients to drive effective data solutions.

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

The AI Data Engineer will design and implement the entire data lifecycle for autonomous AI agents, focusing on video ingestion, processing, and system architecture.

This role involves developing tick data pipelines in Python, serving data to backtesting engines, and ensuring data quality checks are effective.

Design, build, test and maintain ETL/ELT pipelines and analytics warehouse (Snowflake/dbt). Implement data testing, governance, observability and self-service capabilities. Partner with analysts, data scientists and stakeholders, troubleshoot data issues, and mentor colleagues to improve data reliability and analytics processes.

The role involves designing and developing high-performance, real-time data processing systems using Apache Flink and Kafka, ensuring reliability and scalability while collaborating with various teams.