51 to 75 of 413 ETL Jobs in the UK excluding London

workshops, and shape pre-sales proposals (40–50% of the role) Advise senior client stakeholders (CDOs, CIOs, Heads of Data) on data strategy, governance, and platform modernisation Design robust ETL/ELT frameworks with Azure Data Factory , SSIS , Informatica , or IBM DataStage Implement data governance and quality frameworks using Unity Catalog , Profisee , Alation , or similar platforms Provide leadership and mentoring More ❯

platforms. Expertise in modern data tools and frameworks such as Spark, dbt, Airflow, Kafka, Databricks, and cloud-native services (AWS, GCP, or Azure) Understanding of data modeling, distributed systems, ETL/ELT pipelines, and streaming architectures Proficiency in SQL and at least one programming language (e.g., Python, Scala, or Java) Demonstrated experience owning complex technical systems end-to-end, from More ❯

Product Owner in Agile environments. Ideally experience managing Finance and data products or platforms, ideally data warehouses (e.g. Snowflake, BigQuery), or data lakes. Familiarity with data modelling, data pipelines, ETL/ELT processes, and APIs. Strong understanding of data quality frameworks, data contracts, and lineage. Proficient in using analytics and BI tools (e.g., Tableau, Power BI, Looker) to drive product More ❯

Product Owner in Agile environments. Ideally experience managing Finance and data products or platforms, ideally data warehouses (e.g. Snowflake, BigQuery), or data lakes. Familiarity with data modelling, data pipelines, ETL/ELT processes, and APIs. Strong understanding of data quality frameworks, data contracts, and lineage. Proficient in using analytics and BI tools (e.g., Tableau, Power BI, Looker) to drive product More ❯

Product Owner in Agile environments. Ideally experience managing Finance and data products or platforms, ideally data warehouses (e.g. Snowflake, BigQuery), or data lakes. Familiarity with data modelling, data pipelines, ETL/ELT processes, and APIs. Strong understanding of data quality frameworks, data contracts, and lineage. Proficient in using analytics and BI tools (e.g., Tableau, Power BI, Looker) to drive product More ❯

various sources and supports diverse analytical needs, while optimizing costs and meeting business requirements. Implementing Data Engineering Pipelines: Design and develop data pipelines for data extraction, transformation, and loading (ETL) processes, ensuring data quality and consistency. Enabling Data Intelligence and Analytics: Build and maintain data warehouses, data marts, and data lakes to support business intelligence and data analytics initiatives. Supporting More ❯

to RfP response. Ability to be a SPOC for all technical discussions across industry groups. Excellent design experience, with entrepreneurship skills to own and lead solutions for clients Excellent ETL skills, Data Modeling Skills Excellent communication skills Ability to define the monitoring, alerting, deployment strategies for various services. Experience providing solution for resiliency, fail over, monitoring etc. Good to have More ❯

focused but other Cloud technologies such as Oracle andAmazon Web Services (AWS) are usedin FCDO. The successful candidates will build complex data pipelines (both Extract Transform and Load ETL and Extract Load and Transform ELT ) in the Azure cloud platforms. You will work with structured and unstructured data, data lakes, data warehouses to service operational and analytical business needs. The More ❯

focused but other Cloud technologies such as Oracle andAmazon Web Services (AWS) are usedin FCDO. The successful candidates will build complex data pipelines (both Extract Transform and Load ETL and Extract Load and Transform ELT ) in the Azure cloud platforms. You will work with structured and unstructured data, data lakes, data warehouses to service operational and analytical business needs. The More ❯

programming languages such as Python and R. Experience working with cloud-based data platforms, such as Snowflake or Databricks is preferred. Expertise in using T-SQL to interrogate and extract data through complex queries and stored procedures. A comprehensive understanding of databases, query optimisation, load monitoring, the Microsoft BI Stack and ETL frameworks. Technical expertise in data mining, data auditing More ❯

programming languages such as Python and R. · Experience working with cloud-based data platforms, such as Snowflake or Databricks is preferred. · Expertise in using T-SQL to interrogate and extract data through complex queries and stored procedures. · A comprehensive understanding of databases, query optimisation, load monitoring, the Microsoft BI Stack and ETL frameworks. · Technical expertise in data mining, data auditing More ❯

and management Proficient SQL and/or Python capabilities - minimum 2-3 years hands-on experience Comprehensive Data Engineering background - proven track record in enterprise data solutions Experience with ETL processes and data transformation , preferably using Databricks Strong foundation in Data Warehousing architectures and dimensional modeling Familiarity with batch processing from relational database sources Communication & Collaboration Skills of the Data More ❯

ll play a pivotal role in shaping how vital geospatial and property data is structured, visualised and applied. What You’ll Be Doing: Analyse large-scale, complex datasets to extract insights, trends, and improvement opportunities Create impactful dashboards, reports, and data visualisations to support business and customer decisions Collaborate with Data Engineers, PMs, and stakeholders to support the development of … ArcGIS, etc.) Advanced Excel skills; experience with Python or R is a strong plus Strong communicator – able to explain technical insights to non-technical audiences with clarity Understanding of ETL processes, data quality assurance, and working closely with Data Engineers Comfortable operating in agile teams and delivering in iterative cycles Cloud knowledge (especially AWS) is a plus Why Apply? This More ❯

data platforms in cloud using Azure D&A stack, Databricks and Azure Open AI solution. Proficiency in coding (Python,PL/SQL, Shell Script) relational and non-relational databases, ETL tooling (such as Informatica), scalable data platforms. Proficiency in Azure Data and Analytics stack; working knowledge on AWS and GCP data solutions. Good understanding of deploying AI solutions in Azure More ❯

knowledge of Microsoft Fabric, Azure Data Factory, Power BI, and related Azure tools Strong proficiency in SQL, Spark SQL, and Python for data processing and automation Solid understanding of ETL/ELT workflows, data modelling, and structuring datasets for analytics Experience working with large, complex datasets and APIs across formats (CSV, JSON, Parquet, etc) Familiarity with workflow automation tools (eg More ❯

data platforms in cloud using Azure D&A stack, Databricks and Azure Open AI solution. Proficiency in coding (Python, PL/SQL, Shell Script) relational and non-relational databases, ETL tooling (such as Informatica), scalable data platforms. Proficiency in Azure Data and Analytics stack; working knowledge on AWS and GCP data solutions. Good understanding of deploying AI solutions in Azure More ❯

regulatory requirements specific to the public sector. Required education None Preferred education Bachelor's Degree Required technical and professional expertise Responsibilities: Design, build, and maintain scalable data pipelines and ETL processes. Collaborate with data scientists and engineers to integrate complex data systems. Ensure data quality, accuracy, and reliability through testing and validation procedures. Develop and implement data storage solutions, including More ❯

Architecture is highly desirable; however, a Senior Data Engineer eager to transition into this domain will also be considered. Key Responsibilities: Oversee and lead the design and implementation of ETL/ELT processes to ingest data from the new ERP system into Snowflake. Architect and develop the Snowflake data warehouse to support reporting and analytics, incorporating existing SQL Server-based … system architecture models for seamless data integration, storage, processing, and analytics. Business Analysis: Ability to translate stakeholder requirements into strategic application plans. Business Intelligence: Understanding of data lifecycle from ETL to insight generation. IT Security: Awareness of security challenges and mitigation techniques. Effective Governance: Managing projects, processes, and stakeholder relationships. Service and Supplier Management: Providing high-quality service management and … external vendor oversight. Key Skills & Experience: Essential: Experience with ETL/ELT tools (Matillion preferred) Proficiency with SQL Server and Snowflake or similar cloud data warehousing solutions (Azure, AWS, etc.) Experience supporting analytics and reporting using Kimball methodology Experience with data migration and business logic mapping Proven ability to convert business requirements into solutions Experience with Power BI Desirable: Experience More ❯

a Data Warehouse Engineer , you will have the following responsibilities: Design, develop, and maintain scalable data warehouse architecture and solutions to consolidate data from multiple sources. Build and optimize ETL pipelines using modern tools, automation and best practices. Develop and maintain dashboards, visualizations, and reports using Power BI. Collaborate with business stakeholders to gather requirements, translate them into data solutions … contribute to the continuous improvement of data architecture and standards. THE CANDIDATE The ideal Data Warehouse Engineer will possess the following skills: 2+ years of experience in data warehousing, ETL development, and business intelligence reporting. Strong experience with Power BI, including DAX, Power Query, and dashboard development. Proficiency in SQL and data modelling techniques. Strong analytical and problem-solving skills More ❯

Key Responsibilities Lead development of data pipelines and solutions using Databricks, Python, and SQL Design and maintain data models supporting analytics and business intelligence Build and optimise ELT/ETL processes on AWS or Azure Collaborate closely with analysts, architects, and stakeholders to deliver high-quality data products Champion best practices in testing, CI/CD, version control, and infrastructure More ❯

Key Responsibilities Lead development of data pipelines and solutions using Databricks, Python, and SQL Design and maintain data models supporting analytics and business intelligence Build and optimise ELT/ETL processes on AWS or Azure Collaborate closely with analysts, architects, and stakeholders to deliver high-quality data products Champion best practices in testing, CI/CD, version control, and infrastructure More ❯

using industry level best practices.Reporting to the Platform and Engineering Manager, the candidate will be required to design and manage data warehousing solutions, including the development of data models, ETL processes and data integration pipelines for efficient data consolidation, storage and retrieval, providing technical guidance and upskilling for the team, and conducting monitoring and optimisation activities. If you’re a … winning employer, apply to join #TeamAldi today! Your New Role: Project Management of demands and initiatives Lead the design and implementation of data warehousing Design and develop data models, ETL processes and data integration pipelines Complete Data Engineering end-to-end ownership of demand delivery Provide technical guidance for team members Providing 2nd or 3rd level technical support About You More ❯

a senior capacity. Strong hands-on experience with the Azure data ecosystem (ADF, Synapse, SQL, etc.). Proficiency in Microsoft technologies including Power BI. Solid understanding of data modelling, ETL/ELT pipelines, and cloud data storage. Strong communication and stakeholder engagement skills - ability to turn data into business strategy. Desirable: Background in a commercial, customer-centric, or high-growth More ❯

role. Strong hands-on expertise with: ServiceNow (data models, integration, reporting) Data Migration tools and best practices Solid knowledge of Elastic Search , indexing strategies, and query optimization. Experience with ETL/ELT tools and data pipeline orchestration. Strong understanding of data modeling (conceptual, logical, and physical). Proficiency in SQL and one or more scripting/programming languages (e.g., Python More ❯

team culture. Day-to-Day Responsibilities Infrastructure & Automation: Deploy and manage infrastructure using Bicep/Terraform , GitHub Actions , and PowerShell/DSC . Data Engineering: Architect and implement scalable ETL/ELT solutions; model schemas, optimize performance, and apply lakehouse best practices. Security & Resilience: Implement best-practice cloud security (NSGs, Defender, Conditional Access), automate DR/backups, and run quarterly More ❯