Top Data Engineer Jobs in London

As a Data Engineer at Wheely, you will enhance the Data team by implementing best practices for architecture, optimizing the codebase with dbt and LookML, and evolving data integration pipelines using Airbyte and Debezium. You will also ensure data quality and collaborate on feature requests, focusing on improving performance and code quality in a team-oriented environment.

As a Data Engineer, you'll design and maintain data pipelines, collaborate with teams to address misuse issues, and improve system efficiency.

As a Data Engineer at Epic Games, you'll design, build, and maintain data infrastructure for machine learning, manage AWS infrastructure, and optimize data pipelines for efficiency and reliability while collaborating with product teams.

As Principal Data Engineer, you'll drive data strategy and infrastructure evolution, optimize data systems, and lead strategic engineering projects for improved decision-making.

As a Data Engineer, you will develop and implement data engineering pipelines for public sector clients, ensuring data quality and compliance while designing effective data solutions.

As a Data Engineer at Kroo, you will enhance the data analytics solution, design a company-wide data model, and maintain an efficient data stack. Collaborating with various stakeholders, you will ensure data quality and facilitate informed decision-making across the organization.

As a Data Engineer at Veeva Systems, you will enhance data pipelines and improve the data processing platform, collaborating closely with data science teams and taking responsibility for features and architectural enhancements.

The Data Analyst will enhance data access, design data solutions, and provide actionable insights while guiding team members and ensuring data quality.

The Senior Data Engineer will build and maintain data pipelines for alternative commodity and macro data, collaborate with trading teams to understand data needs, develop scalable data architectures, ensure data accuracy, and enhance data processing workflows.

The Data Engineer will enhance Copper's Business Intelligence capabilities by designing and building reporting models, dashboards, and managing stakeholder relationships. Responsibilities also include data management, analytics, and supporting ad-hoc reporting requests. The role emphasizes adopting best practices to support data-driven decision making within the organization.

The Associate Data Engineer will build financial and Business Intelligence reports, support data visualisation, and assist in promoting data culture within the company. Responsibilities include developing data models, enhancing analytics capabilities, and fulfilling ad-hoc reporting requests.

The Data Engineer will design, develop, and maintain data pipelines for processing and storing datasets used in AI models. Responsibilities include data cleaning, infrastructure management, and implementing MLOps best practices, all while working collaboratively with engineers and data scientists.

The Senior Data Engineer will build and maintain data integration pipelines, collaborate with traders and researchers to understand their data needs, develop scalable data architectures, and ensure data accuracy and reliability, primarily focusing on alternative commodity and macro data.

The Data Engineer will analyze, clean, manage, and share data to support trading activities, focusing on ETL processes and data quality. The role requires collaboration with traders and software engineers to derive insights from diverse datasets.

The Data Engineer will develop and manage data architecture, integrate new data sets, transition existing data to a new technology stack, and lead analysis using various techniques, including machine learning. They will also support data ingestion processes and collaborate with commercial teams to optimize data usage and address gaps.

The Data Engineer will design and implement data flows and pipelines in a cloud environment, integrating data from various sources, building complex data models, and ensuring high-quality code for scalable platforms. Collaboration with analysts and fellow engineers is crucial, along with adopting DevOps practices and continuously learning new technologies.

As a Data Engineer, you will design and maintain large-scale data pipelines using Microsoft Fabric and Databricks, ensuring data quality and integration across the organization.