You will design, develop, and support data integration, warehousing, and reporting solutions for a secure government programme. The role involves working with Oracle databases, ETL processes, and data quality, within a complex enterprise environment.
This role involves leading the final stages of a migration from a legacy data warehouse to Microsoft Fabric, with responsibilities including testing data outputs, debugging discrepancies, and implementing fixes. Post go-live, the engineer will build data pipelines and support ongoing development and reporting needs. The role requires hands-on technical delivery within a modernising data environment.
This role involves designing and building data pipelines using Microsoft Fabric, supporting the end-to-end implementation of a new enterprise data platform, and developing data models and integration processes. The project is a greenfield initiative, offering the opportunity to shape best practices and deliver a modern data environment from scratch.
This role involves joining a major data transformation programme, focusing on the final stages of migrating from a legacy data warehouse to a new Microsoft Fabric environment. Responsibilities include testing outputs, debugging data differences, and making remedial changes. Post go-live, the role shifts to supporting and developing data pipelines and delivering data and reporting requirements.
This role involves building and optimizing a modern AWS data platform, integrating NetSuite and other financial data sources, and developing scalable ETL/ELT pipelines. You'll work closely with Data and Finance teams to turn business requirements into reliable data solutions and ensure data quality and monitoring.
This role involves taking ownership of SQL-driven data development and reporting, building and maintaining ETL pipelines using SSIS and Azure Data Factory, and developing Power BI dashboards. You'll support both day-to-day activities and long-term transformation projects, contributing to the modernisation of the data warehouse and the transition to new technologies like Python and Microsoft Fabric.
This role involves leading the modernization of core data platforms using Microsoft Azure technologies, including Azure Synapse, Azure SQL Server, and Microsoft Fabric. You will work on enhancing data pipelines, ensuring data reliability and scalability, and collaborating with BI and analytics teams to support advanced analytics and executive decision-making.
Design and build scalable data pipelines on a cloud-based SaaS platform using PySpark, Airflow, and Azure. Integrate complex data sources and collaborate with stakeholders to deliver a unified data solution. Mentor junior engineers and contribute to the evolution of a modern data architecture.
As a Senior Data Engineer, you will design, build, and scale robust data platforms using AWS, Snowflake, and dbt. You will lead the development of data pipelines, models, and architecture, ensuring performance, reliability, and scalability while collaborating with cross-functional teams.
This Senior Data Engineer role involves building, integrating, and transforming data to support business intelligence and strategic growth. You will own the data lake, develop integrations, and work closely with the Finance and Commercial teams to shape the future of the data platform using Microsoft Fabric and Azure technologies.
This role involves designing, developing, and optimizing modern data platforms using Azure Databricks. Responsibilities include building scalable data pipelines, managing large datasets, and implementing Lakehouse architectures on Azure Data Lake Storage Gen2. The position offers a hybrid work pattern with 3 days on-site in Nottingham.
This role focuses on leading enterprise data warehouse migrations from legacy systems to the Databricks Intelligence Platform. The Senior Solutions Architect will design technical go-to-market strategies, develop scalable migration frameworks, and act as a top-tier technical advisor for complex customer transitions across EMEA. Key responsibilities include building automated assessment tools, mentoring regional teams, and bridging field feedback into product development.
This role involves designing, developing, and supporting scalable data solutions using Azure Databricks, SQL, PySpark, and Python. You will build and maintain ETL/ELT pipelines, support data quality processes, and integrate Azure services. The position requires strong hands-on experience with Azure Databricks and data engineering, with a focus on large-scale data pipelines and platform performance.
This role involves refreshing and redocumenting enterprise data warehouse models, creating diagrams, and ensuring version control. You'll work closely with data category management to catalogue data, document flows, and map data movement across applications using tools like Sparx Enterprise Architect or Orbus iServer. The focus is on conceptual and logical data modelling rather than hands-on engineering.
This role involves ensuring data quality and governance within a global travel company's data team. Responsibilities include automating data quality checks, maintaining data dictionaries, collaborating with technical and business teams, and analyzing complex datasets to inform business decisions.
