73 Data Engineer jobs in United Kingdom available for remote work from home. Apply for positions such as Senior Data Engineer - Terminal.exe, Data Engineer III - FMX, UniData/ UniVerse Data Engineer (Remote) and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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You will design and build ELT pipelines to move data from terminal operating systems into a centralized Azure-based platform. Additionally, you will develop transformation layers and maintain a standardized data model to ensure data quality and consistency across global terminals.
You will build and govern data ingestion pipelines using Python, Airflow, and cloud warehouse technologies like Snowflake or Databricks. Additionally, you will investigate pipeline failures, mentor junior engineers, and collaborate with stakeholders to ensure data reliability and security.
The engineer will design, develop, and optimize UniData/Universe applications to manage complex commission-processing logic and distributor hierarchies. They will also perform data extraction, transformation, and reconciliation while ensuring the accuracy of high-volume transactional data.
You will build and maintain automated data pipelines and develop algorithms to extract relevant information from websites and images. Additionally, you will manage the data infrastructure and create analytics reports for internal and external stakeholders.
You will build and maintain ELT pipelines while monitoring their health and data freshness within a multi-tenant environment. Additionally, you will collaborate with data and product teams to extend modeling layers and support CI/CD and ingestion projects.
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Lead and review the electrical design of hyperscale and mission-critical data centres across all project phases while managing multidisciplinary external consultants. Oversee utility coordination, permitting, and integrated systems testing to ensure project delivery meets design intent and operational requirements.
You will design and maintain reliable data pipelines, internal tools, and APIs to support analytics and machine learning applications. You will collaborate with product and engineering teams to ensure data infrastructure is efficient and scalable.
The Forward Deployed Engineer will partner with business stakeholders to rapidly build and deploy automation and data-driven AI solutions. This role involves full-stack engineering, including data pipelining, backend development, and creating interactive applications to solve complex business problems.
Design and build the harness environment to steer AI coding agents toward high-quality, maintainable, and secure software output. Establish feedback loops, automated testing infrastructure, and quality gates to ensure agent-generated code meets production standards.
You will design, build, and own scalable data pipelines across the modern data stack from ingestion to delivery. Additionally, you will lead architectural decisions and ensure data quality, lineage, and observability for critical incentive payouts.
The role involves writing production Python code to build and maintain data pipelines for the Insights platform. It also requires providing technical leadership to set the platform's direction and improving engineering standards across the team.
Lead the technical design and delivery of enterprise-scale cloud-native data platforms and serverless applications on AWS. Drive engineering excellence through technical governance, mentoring multidisciplinary teams, and implementing secure, scalable data pipelines.
Lead the design and development of scalable data processing and persistence components within agile teams. Provide technical leadership, enforce development best practices, and manage the performance and career growth of junior staff.
Design and develop large-scale data processing and persistence software components within agile teams. Provide technical leadership, mentor team members, and ensure software meets non-functional requirements and operational readiness.
Build and maintain resilient streaming and batch data pipelines to ingest, normalize, and distribute market and trading data. Develop self-serve tooling and data governance frameworks to ensure high-quality, observable, and performant data products across the organization.
You will define the architecture for the data platform and lead the design of scalable, low-latency pipelines for high-volume payment transactions. Additionally, you will mentor senior engineers and partner with cross-functional teams to ensure data reliability and business value.
You will design and maintain a central data ecosystem to provide a unified source of truth across 60+ global sub-brands. This involves building scalable ETL/ELT pipelines and establishing robust data governance frameworks to support business intelligence and AI initiatives.
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As a Senior Data Engineer, you will deliver on complex projects, either individually or by leading small teams. You will manage customer relationships and support pre-sales processes while mentoring junior engineers.
The Instrumentation and Controls Project Engineer will design instrumentation and control systems for Data Centers, managing tasks related to Building Management System design and specifications. This role involves communication and coordination with various engineering disciplines and stakeholders to ensure proper design and construction.
The Data Analytics Engineer will design and maintain scalable data models and semantic layers to support consistent self-service analytics. They will also collaborate with cross-functional teams to implement data quality controls and ensure business rules are transparent and well-documented.
You will design, build, and operate secure, scalable cloud-native data platform services and components for public sector and utility projects. This involves automating infrastructure, managing data pipelines, and ensuring the reliability and performance of production environments.
Design, build, and maintain backend services for the data layer, ensuring performance and scalability across relational databases and search engines. Lead engineering initiatives end-to-end while collaborating with cross-functional teams to deliver high-quality solutions.
You will build and govern the data foundation by implementing ingestion pipelines and managing data flow from source to warehouse. Additionally, you will investigate pipeline failures, perform code reviews, and support data security and governance initiatives.
You will design and improve financial risk scoring algorithms while building scalable data pipelines to process massive datasets. Additionally, you will deploy production-ready machine learning models for fraud detection and behavioral analysis while ensuring model stability and explainability.
The Data Solutions Engineer will design, develop, and maintain data models and analytical reports to support business intelligence and operational needs. They will also collaborate with IT and engineering teams to enforce data governance standards and ensure seamless integration across data systems.
You will own the lifecycle of data platform infrastructure, including architecture, deployment, capacity planning, and incident response. You will also focus on operational automation to reduce manual work and improve system reliability.
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Design and build scalable quality frameworks and infrastructure for human data used in training advanced AI models. Act as a strategic partner to clients and AI labs to translate model needs into robust evaluation strategies and annotation schemas.
Lead quality assurance and define the test strategy for a large-scale cloud data engineering programme on AWS. Oversee automated testing frameworks, data pipeline validation, and risk management within a CI/CD environment.
Embedded within delivery teams to provide real-time engineering rigor, reviewing technical decisions and code to ensure enterprise scalability. Bridges the gap between business-built AI capabilities and production-ready software through integration design and data governance.
Design and scale mission-critical market data systems and public APIs for stocks, options, crypto, and forex. Focus on reducing latency, implementing resilient backend services, and maintaining high software quality through code reviews and testing.
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