51 to 75 of 860 ETL Jobs in London

scalable data systems (data warehouses, data lakes, and data pipelines). Proficiency in cloud platforms such as AWS, Azure, or Google Cloud. Experience with ETL/ELT tools and real-time data processing. Strong knowledge of SQL, NoSQL databases, and data modeling techniques. Familiarity with BI tools like Tableau, Power More ❯

to 10+ years' extensive experience in SQL Server data warehouse or data provisioning architectures. Advanced SQL query writing & SQL procedure experience. Experience developing ETL solutions in SQL Server including SSIS & T-SQL. Experience in Microsoft BI technologies (SQL Server Management Studio, SSIS, SSAS, SSRS). Experience of data/system More ❯

Data Skills: Proficiency in using analytics tools (e.g., Power BI, SQL, Python) for data transformation, visualization, and predictive modelling. Experience with data integration and ETL processes, and familiarity with project management systems like PRISM or Primavera. Problem Solving & Insight Generation: Strong ability to interpret complex data sets, identify issues, and More ❯

a culture of technical excellence within the team. Data Engineering Expertise: Deep understanding of data engineering principles and best practices, including data modeling, observable ETL/ELT processes, data warehousing, and data governance. Proficiency in data manipulation languages (e.g., SQL/DBT) and programming languages relevant to data engineering (e.g. More ❯

to: Design and Develop Data Pipelines: Create robust pipelines to ingest, process, and transform data, ensuring it is ready for analytics and reporting. Implement ETL/ELT Processes: Develop Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) workflows to seamlessly move data from source systems to Data Warehouses, Data More ❯

in Databricks, PySpark, Knowledge Graphs, Neo4J (Graph database and analytics), Power BI, SSRS, Azure Data Factory, and AI technologies. Strong understanding of data architecture, ETL processes, and data governance. Leadership Skills: Demonstrated ability to lead and inspire teams, manage complex projects, and drive organisational change. Analytical Skills: Strong analytical and More ❯

in Databricks, PySpark, Knowledge Graphs, Neo4J (Graph database and analytics), Power BI, SSRS, Azure Data Factory, and AI technologies. Strong understanding of data architecture, ETL processes, and data governance. Leadership Skills: Demonstrated ability to lead and inspire teams, manage complex projects, and drive organisational change. Analytical Skills: Strong analytical and More ❯

in Databricks, PySpark, Knowledge Graphs, Neo4J (Graph database and analytics), Power BI, SSRS, Azure Data Factory, and AI technologies. Strong understanding of data architecture, ETL processes, and data governance. Leadership Skills: Demonstrated ability to lead and inspire teams, manage complex projects, and drive organisational change. Analytical Skills: Strong analytical and More ❯

the planning and implementation of all data governance initiatives. The suitable candidate will have experience with SQL databases along with data modelling, data scraping, ETL, scripting and data support as well as direct experience implementing data governance initiatives within cloud platforms e.g. DataBricks. This is a hands-on role that More ❯

the planning and implementation of all data governance initiatives. The suitable candidate will have experience with SQL databases along with data modelling, data scraping, ETL, scripting and data support as well as direct experience implementing data governance initiatives within cloud platforms e.g. DataBricks. This is a hands-on role that More ❯

the planning and implementation of all data governance initiatives. The suitable candidate will have experience with SQL databases along with data modelling, data scraping, ETL, scripting and data support as well as direct experience implementing data governance initiatives within cloud platforms e.g. DataBricks. This is a hands-on role that More ❯

Principal Data Scientist to operationalise RAG systems, fine-tune data retrieval processes, and optimise training datasets for AI model development. Automation and Optimisation: Automate ETL (Extract, Transform, Load) processes, reduce manual intervention, and continuously identify opportunities to enhance the efficiency and reliability of data workflows. Support Research and Prototyping: Build More ❯

Principal Data Scientist to operationalise RAG systems, fine-tune data retrieval processes, and optimise training datasets for AI model development. Automation and Optimisation: Automate ETL (Extract, Transform, Load) processes, reduce manual intervention, and continuously identify opportunities to enhance the efficiency and reliability of data workflows. Support Research and Prototyping: Build More ❯

Principal Data Scientist to operationalise RAG systems, fine-tune data retrieval processes, and optimise training datasets for AI model development. Automation and Optimisation: Automate ETL (Extract, Transform, Load) processes, reduce manual intervention, and continuously identify opportunities to enhance the efficiency and reliability of data workflows. Support Research and Prototyping: Build More ❯

. Experience with modern data platforms, including data lakes, data warehouses (e.g., Snowflake, Redshift, BigQuery), and real-time data processing. Proficiency in data modeling, ETL/ELT pipelines, and data integration tools. Strong understanding of security, compliance, and governance for data and cloud platforms. Hands-on experience with analytics and More ❯

third-party providers. Knowledge of Lloyds Insurance and Reinsurance, Finance GAAP, Actuarial Reserves, Regulatory Reports, Databases (Data Warehouse, T-SQL, SSIS, SQL Server 2019), ETL processes with Databricks, Programming languages (e.g., Python), AWS, Agile methodologies, Jira, and MS Office products. Educational background with a BSc degree or higher in a More ❯

On a daily basis your varied role will include, but will not be limited to: Design, build, and optimize high-performance data pipelines and ETL workflows using tools like Azure Synapse, Azure Databricks or Microsoft Fabric. Implement scalable solutions to ingest, store, and transform vast datasets, ensuring data availability and More ❯

On a daily basis your varied role will include, but will not be limited to: Design, build, and optimize high-performance data pipelines and ETL workflows using tools like Azure Synapse, Azure Databricks or Microsoft Fabric. Implement scalable solutions to ingest, store, and transform vast datasets, ensuring data availability and More ❯

implemented efficient and scalable data models that support reporting and analytics requirements. • Used Power Query (or similar tools) for data extraction, transformation, and loading (ETL) processes to prepare data for analysis. • Demonstrable skill in performing data analysis on large datasets and preferably worked in data engineering roles to analyse and More ❯

implemented efficient and scalable data models that support reporting and analytics requirements. Used Power Query (or similar tools) for data extraction, transformation, and loading (ETL) processes to prepare data for analysis. Demonstrable skill in performing data analysis on large datasets and preferably worked in data engineering roles to analyse and More ❯

BI reports. Connect Power BI to various data sources, including MongoDB, SQL databases, Excel, and cloud services. Design and implement efficient data models and ETL processes using Power Query and DAX. Optimize Power BI performance by fine-tuning data models. Collaborate with data analysts and business stakeholders to gather and More ❯

or Logic Apps. Preferred Qualifications: Experience integrating financial, cloud, and operational data from multiple systems. Familiarity with Azure Data Factory, SQL Server, or similar ETL platforms. FinOps Certified Practitioner certification More ❯

reporting development (advanced/expert levels only). Key Tools & Technologies Visualization Tools: Tibco Spotfire, Tableau, Power BI, or QlikView Data Management & Querying: SQL, ETL pipelines, Data Warehousing (e.g., ODW) Scripting/Programming: Iron Python, R, R Shiny, SAS Collaboration & Platforms: SharePoint, clinical trial data platforms Qualifications Entry Level: Bachelor More ❯

reporting development (advanced/expert levels only). Key Tools & Technologies Visualization Tools: Tibco Spotfire, Tableau, Power BI, or QlikView Data Management & Querying: SQL, ETL pipelines, Data Warehousing (e.g., ODW) Scripting/Programming: Iron Python, R, R Shiny, SAS Collaboration & Platforms: SharePoint, clinical trial data platforms Qualifications Entry Level: Bachelor More ❯

reporting development (advanced/expert levels only). Key Tools & Technologies Visualization Tools: Tibco Spotfire, Tableau, Power BI, or QlikView Data Management & Querying: SQL, ETL pipelines, Data Warehousing (e.g., ODW) Scripting/Programming: Iron Python, R, R Shiny, SAS Collaboration & Platforms: SharePoint, clinical trial data platforms Qualifications Entry Level: Bachelor More ❯