Latest UK roles, updated daily.
Design and govern enterprise-scale data architectures across hybrid and cloud environments, including data lakes, warehouses, and modern data pipelines. Provide technical leadership on data management frameworks, cloud migration, and AI-enabled analytics solutions within an Agile transformation programme. Collaborate with stakeholders and delivery teams to ensure robust, scalable data platforms aligned with governance and business needs.
Job Title: DV Cleared Data EngineerLocation: BathDuration: 12 monthsRate: Up to £500 per dayMust be willing and eligible to go through the DV clearance processOur client, a reputable organisation supporting high-profile government programmes, is hiring a DV Cleared Data Engineer...
This role focuses on driving adoption of Databricks Lakebase, a fully managed Postgres service, by partnering with account teams to identify and close sales opportunities. The specialist will engage technical and business stakeholders across platform, data, and IT teams to position Lakebase as a modern operational data foundation for AI-native and real-time applications. Key responsibilities include leading proof-of-value initiatives, navigating complex sales cycles, and enabling field teams to scale Lakebase expertise.
This role involves driving adoption of Databricks Lakebase, a fully managed Postgres service, by partnering with account teams to identify and close sales opportunities across platform, data, and application teams. The specialist will lead technical and business conversations, run proof-of-value engagements, and position Lakebase as a modern solution for AI-native and real-time operational workloads. Success requires aligning technical capabilities with business outcomes while enabling broader sales teams and shaping go-to-market strategy.
Design and maintain data-driven backend applications using Python and SQL, with a focus on data lakes, lakehouse architectures, and ETL/ELT pipelines. Develop robust database solutions and APIs while collaborating with data engineering and analytics teams. Work across modern data platforms to ensure data quality, governance, and scalable integration.
Design and build end-to-end data-intensive applications, including APIs, data pipelines, and cloud infrastructure across AWS and Azure. Develop and maintain data warehouses and support AI-ready platforms while collaborating with consultants and analysts. Focus on scalable business solutions using modern data and full-stack technologies.
Design and maintain scalable data pipelines on Azure to ingest and process data from multiple sources into Databricks for analytics, reporting, and AI use cases. Collaborate with data analysts, modellers, and stakeholders in an Agile environment to deliver trusted, governed data products. Focus on data quality, security, and alignment with enterprise architecture and governance standards.
This role involves building and maintaining scalable data pipelines for AI/ML-driven user experience projects, using Google Cloud Platform and tools like Airflow and Cloud Composer. The analyst will ensure data quality and system reliability through monitoring with Monte Carlo, Looker, Splunk, and NewRelic, while collaborating closely with product engineering and data science teams. Responsibilities include data ingestion, pipeline orchestration, and technical documentation to support cross-functional data initiatives.
This role involves designing and building scalable data pipelines on Azure and Databricks, using Delta Lake and Medallion architecture. You'll own data models across multiple layers, implement CI/CD via Azure DevOps, and support integration with Microsoft Fabric and OneLake. The position emphasizes technical leadership, engineering best practices, and end-to-end ownership of a modern data platform.
Design and build secure, scalable data pipelines for a major UK public sector digital transformation programme, focusing on data integration, transformation, and curation using AWS and enterprise ETL tools. Work within Agile, multidisciplinary teams to deliver high-quality data products supporting AI capabilities and modern data platforms.
The role involves working with sales and product data to measure year-on-year subscription growth, focusing on accurate categorisation of retired and active products. The engineer will ensure data integrity across historical and current sales datasets within an Azure Databricks environment. Key tasks include data mapping, pipeline development, and alignment with business-defined metrics for uplift, upsell, cross-sell, and cancellations.
Leads the design and operation of data platforms and delivery of business-ready insights, combining data engineering and analytics to support strategic decision-making. Manages data pipelines, data lake architecture, and Power BI reporting while leading a technical team and ensuring data governance, quality, and compliance. Promotes self-service analytics and collaborates with stakeholders to deliver measurable business value.
Design and build production-grade data pipelines using Microsoft Fabric, PySpark, and Azure technologies for high-regulation clients. Develop Lakehouse and Warehouse solutions on OneLake, implement data governance, and collaborate with data architects and scientists on large-scale transformation projects. Focus on scalable, cloud-native engineering practices with strong emphasis on quality and CI/CD.
This role involves designing and maintaining CI/CD pipelines, automating Azure cloud infrastructure, and supporting a government client's data platform using DevOps practices. The engineer will implement Infrastructure as Code, troubleshoot operational issues, and mentor Agile delivery teams. Key focus areas include Azure Data Factory, Synapse Analytics, and monitoring with Prometheus and Grafana.
The Energy Analytics Engineer will design and maintain data pipelines using Azure-based tools, automate data ingestion from APIs, and support reporting and analytics for energy and sustainability initiatives. The role involves close collaboration with cross-functional teams to deliver robust data models, ensure data quality, and enable data-driven decision-making. A key focus is on enabling carbon reporting and driving digital solutions that support Veolia’s ecological transformation goals.
