1 to 25 of 1,265 ETL Jobs in the UK

Mathematics Preferred : Experience in the financial services industry, preferably with exposure to market risk or counterparty credit risk applications Experience in ETL (extract, transform and Load) development Some Cloud experience will be a nice plus. Personal Attributes: Strong analytical, verbal and written communication skills Self-starter and entrepreneurial in approach More ❯

Mathematics Preferred : Experience in the financial services industry, preferably with exposure to market risk or counterparty credit risk applications Experience in ETL (extract, transform and Load) development Some Cloud experience will be a nice plus. Personal Attributes: Strong analytical, verbal and written communication skills Self-starter and entrepreneurial in approach More ❯

to data storage and processing systems. This includes automating data collection, cleaning, and integration processes to support analytics and reporting needs. Develop and optimize ETL processes: Create and enhance ETL (Extract, Transform, Load) processes to extract data from multiple sources, transform it into a usable format, and load it into … Perform regular database tuning, indexing, and query optimization to maintain high performance and reliability. Create and maintain documentation: Develop comprehensive documentation for data pipelines, ETL processes, and data architecture. Ensure that documentation is up-to-date, clear, and accessible to relevant stakeholders, facilitating knowledge sharing and continuity. Monitor and troubleshoot More ❯

Good understanding with Microsoft BI toolset, including O365 tools and PowerPlatform (PowerApps/Power Automate/Power BI). • Good understanding of Azure cloud ETL toolset, including Azure SQL Server, Azure Data Factory, Datalake. • Familiar with Cloud technologies including Microsoft Azure Cloud infrastructure, data stores connections, cloud functions concepts. • Experience More ❯

services. Knowledge of using PySpark in notebooks for data analysis and manipulation. Strong proficiency with SQL and data modelling. Experience with modern ELT/ETL tools within the Microsoft ecosystem. Solid understanding of data lake and lakehouse architectures. Hands-on experience with Power BI for data integration and visualisation. Familiarity More ❯

Modelling, Database & Data Platform Design. Proficiency in creating logical & physical data models. Knowledge of relational (SQL) and non-relational (NoSQL) database systems. Understanding of ETL/ELT Processes. Solid understanding of Data Integration & Architecture. Experience with data integration. Data warehousing concepts. Data flow design. Experience working with cloud computing on More ❯

expert in cloud data engineering providing technical guidance and mentorship to the team. Drive the design development and implementation of complex data pipelines and ETL/ELT processes using cloud-native technologies (e.g. AWS Glue AWS Lambda AWS S3 AWS Redshift AWS EMR). Develop and maintain data quality checks More ❯

Stream Analytics, and Event Hub. Experience working with the Microsoft Azure cloud-based ecosystem Experience in extracting data from heterogeneous data sources by using ETL tools Experience in creating and managing SSAS Tabular models, creating Dimension and Fact Tables. Finance or Insurance domain Reporting Tools: Power BI, Cognos, MicroStrategy. What More ❯

considered for a strong candidate): ADLS, Databricks, Stream Analytics, SQL DW, Synapse, Databricks, Azure Functions, Serverless Architecture, ARM Templates, DevOps. Hands-on experience with ETL/ELT processes and data warehousing. Solid understanding of data security and compliance standards. Experience with DevOps practices and tools (e.g., CI/CD pipelines More ❯

design tools (e.g., Adobe Creative Suite, Figma). Expertise in semantic model optimisation and Power BI capacity management. Strong understanding of dimensional data modelling, ETL processes, and data warehousing. Skilled in SQL, Data Analysis Expression (DAX), Power Query M code. Familiarity with cloud platforms, especially Microsoft Azure, for deploying and More ❯

Azure- The Skills You'll Need to Succeed: Mastery of Data bricks, Python/PySpark and SQL/SparkSQL. Experience in Big Data/ETL (Spark and Data bricks preferred). Expertise in Azure. Proficiency with versioning control (Git preferred). Knowledge of and/or experience with using or More ❯

Azure Data Factory, Azure Synapse Analytics, Azure Data Lake, Azure Databricks and Power BI. Experience with creating low-level designs for data platform implementations. ETL pipeline development for the integration with data sources and data transformations including the creation of supplementary documentation. Proficiency in working with APIs and integrating them More ❯

using Azure based data warehouse technologies such as Azure Data Factory, Analysis Services, SQL server and Azure Synapse. Data Pipeline Creation: Build and optimize ETL/ELT data pipelines using Azure Data Factory, Databricks, or similar services to ensure data is properly ingested, transformed, and loaded into the data warehouse. More ❯

using Azure based data warehouse technologies such as Azure Data Factory, Analysis Services, SQL server and Azure Synapse. Data Pipeline Creation: Build and optimize ETL/ELT data pipelines using Azure Data Factory, Databricks, or similar services to ensure data is properly ingested, transformed, and loaded into the data warehouse. More ❯

using Azure based data warehouse technologies such as Azure Data Factory, Analysis Services, SQL server and Azure Synapse. Data Pipeline Creation: Build and optimize ETL/ELT data pipelines using Azure Data Factory, Databricks, or similar services to ensure data is properly ingested, transformed, and loaded into the data warehouse. More ❯

Factory Azure Data Lake Familiarity with continuous integration, continuous delivery, agile methodologies, and Azure DevOps. Familiarity with optimizing strategies, pipeline architectures, data sets, and ETL/ELT processes. You will likely be Passionate about technology, including the Hymans chosen technology stack (Microsoft development stack, Azure Cloud computing, Data Science technologies More ❯

systems. Support the adoption and optimisation of MDM tools and processes. 4. ETL Development & Data Processing Develop and maintain ETL processes to extract, transform, and load data from diverse sources. Monitor and troubleshoot data flow and processing issues. 5. Data Governance & Quality Assurance Enforce data governance standards and ensure data … to identify root causes and implement effective resolutions. Skills & Experience Essential: Strong experience in developing and maintaining enterprise data warehouses. Proficiency in designing and managing ETL processes and integration pipelines. Practical knowledge of master data management principles. Familiarity with both legacy and cloud-based application environments. Attention to detail with More ❯

transparency and standardization across teams. Data Migration & Transformation: - Lead data migration efforts, particularly during system upgrades or transitions to new platforms. - Define and implement ETL (Extract, Transform, Load) processes for transforming data into usable formats for analytics and reporting. Documentation and Reporting: - Document data architecture designs, processes, and standards for … big data platforms (e.g., Hadoop, Spark, Kafka). • Familiarity with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud). • Expertise in ETL tools and processes (e.g., Apache NiFi, Talend, Informatica). • Proficiency in data integration tools and technologies. • Familiarity with data visualization and reporting tools (e.g., Tableau More ❯

Data Engineer - FinTech Company - Newcastle (Tech Stack: Data Engineer, Databricks, Python, Azure, Power BI, AWS QuickSight, AWS, TSQL, ETL, Agile Methodologies) I’m working with a leading Software House in the FinTech industry, based in Newcastle, who are looking to hire a talented Data Engineer . This is a fantastic More ❯

scalability, robust data governance and optimal performance. Developing innovative solutions: Create PoCs and MVPs for Data & AI solutions focusing on pipeline automation, ELT/ETL processes, and deployment through enterprise data platforms. Crafting compelling user experiences: Blend user-centred design with storytelling to deliver impactful Gen AI/BI, WebApp More ❯

accessibility across the organisation. Key Skills & Experience: Strong hands-on experience with Azure Data Platform technologies (Synapse, Data Lakes, ADF) Expertise in data modelling, ETL/ELT pipeline development, and data integration Proficient in SQL and Python (ideally PySpark) Knowledge of tools such as Power BI, Microsoft Fabric, and DevOps More ❯

with machine learning and predictive analytics. Knowledge of cloud-based data platforms such as AWS, Azure, or Google Cloud. Familiarity with data warehousing and ETL processes. Experience in a business or financial analysis environment. If you are passionate about data-driven decision-making and want to make an impact, we More ❯

Azure Data Factory, Azure Synapse Analytics, Azure Data Lake, Azure Databricks and Power BI. Experience with creating low-level designs for data platform implementations. ETL pipeline development for the integration with data sources and data transformations including the creation of supplementary documentation. Proficiency in working with APIs and integrating them More ❯

Azure Data Factory, Azure Synapse Analytics, Azure Data Lake, Azure Databricks and Power BI. Experience with creating low-level designs for data platform implementations. ETL pipeline development for the integration with data sources and data transformations including the creation of supplementary documentation. Proficiency in working with APIs and integrating them More ❯

sets to meet business and technical requirements. Process Improvement: Identify and implement process enhancements, automate manual tasks, and optimize data delivery. Data Integration: Build ETL infrastructure to ensure smooth data extraction, transformation, and loading. Collaboration: Work alongside stakeholders, including data scientists and analysts, to meet data infrastructure needs. Data Quality More ❯