1 to 25 of 736 ETL Jobs in the UK

implementing data engineering best-practice (e.g., source-to-target mappings, coding standards, data quality, etc.), working closely with the external party who setup the environment . Create and maintain ETL processes, data mappings & transformations to orchestrate data integrations. Ensure data integrity, quality, privacy, and security across systems, in line with client and regulatory requirements. Optimize data solutions for performance and … up monitoring and data quality exception handling. Strong data modelling experience. Experience managing and developing CI/CD pipelines. Experience with Microsoft Azure products and services, and proficiency in ETL processes. Experience of working with APIs to integrate data flows between disparate cloud systems. Strong analytical and problem-solving skills, with the ability to work independently and collaboratively. The aptitude More ❯

implementing data engineering best-practice (e.g., source-to-target mappings, coding standards, data quality, etc.), working closely with the external party who setup the environment . Create and maintain ETL processes, data mappings & transformations to orchestrate data integrations. Ensure data integrity, quality, privacy, and security across systems, in line with client and regulatory requirements. Optimize data solutions for performance and … up monitoring and data quality exception handling. Strong data modelling experience. Experience managing and developing CI/CD pipelines. Experience with Microsoft Azure products and services, and proficiency in ETL processes. Experience of working with APIs to integrate data flows between disparate cloud systems. Strong analytical and problem-solving skills, with the ability to work independently and collaboratively. The aptitude More ❯

implementing data engineering best-practice (e.g., source-to-target mappings, coding standards, data quality, etc.), working closely with the external party who setup the environment . Create and maintain ETL processes, data mappings & transformations to orchestrate data integrations. Ensure data integrity, quality, privacy, and security across systems, in line with client and regulatory requirements. Optimize data solutions for performance and … up monitoring and data quality exception handling. Strong data modelling experience. Experience managing and developing CI/CD pipelines. Experience with Microsoft Azure products and services, and proficiency in ETL processes. Experience of working with APIs to integrate data flows between disparate cloud systems. Strong analytical and problem-solving skills, with the ability to work independently and collaboratively. The aptitude More ❯

implementing data engineering best-practice (e.g., source-to-target mappings, coding standards, data quality, etc.), working closely with the external party who setup the environment . Create and maintain ETL processes, data mappings & transformations to orchestrate data integrations. Ensure data integrity, quality, privacy, and security across systems, in line with client and regulatory requirements. Optimize data solutions for performance and … up monitoring and data quality exception handling. Strong data modelling experience. Experience managing and developing CI/CD pipelines. Experience with Microsoft Azure products and services, and proficiency in ETL processes. Experience of working with APIs to integrate data flows between disparate cloud systems. Strong analytical and problem-solving skills, with the ability to work independently and collaboratively. The aptitude More ❯

appropriate architecture design, opting for modern architectures where possible. Data Modeling: Design and optimize data models and schemas for efficient storage, retrieval, and analysis of structured and unstructured data. ETL Processes: Develop, optimize and automate ETL workflows to extract data from diverse sources, transform it into usable formats, and load it into data warehouses, data lakes or lakehouses. Big Data … teams, including data scientists, analysts, and software engineers, to understand requirements, define data architectures, and deliver data-driven solutions. Documentation: Create and maintain technical documentation, including data architecture diagrams, ETL workflows, and system documentation, to facilitate understanding and maintainability of data solutions. Best Practices: Stay current with emerging technologies and best practices in data engineering, cloud architecture, and DevOps. Mentoring … and Flink. Experience in using modern data architectures, such as lakehouse. Experience with CI/CD pipelines, version control systems like Git, and containerization (e.g., Docker). Experience with ETL tools and technologies such as Apache Airflow, Informatica, or Talend. Strong understanding of data governance and best practices in data management. Experience with cloud platforms and services such as AWS More ❯

closely collaborate with data scientists, analysts, and software engineers to ensure efficient data processing, storage, and retrieval for business insights and decision-making. From their expertise in data modelling, ETL (Extract, Transform, Load) processes, and big data technologies it becomes possible to develop robust and reliable data solutions. RESPONSIBILITIES Data Pipeline Development: Design, implement, and maintain scalable data pipelines for … sources using tools such as databricks, python and pyspark. Data Modeling: Design and optimize data models and schemas for efficient storage, retrieval, and analysis of structured and unstructured data. ETL Processes: Develop and automate ETL workflows to extract data from diverse sources, transform it into usable formats, and load it into data warehouses, data lakes or lakehouses. Big Data Technologies … teams, including data scientists, analysts, and software engineers, to understand requirements, define data architectures, and deliver data-driven solutions. Documentation: Create and maintain technical documentation, including data architecture diagrams, ETL workflows, and system documentation, to facilitate understanding and maintainability of data solutions. Best Practices: Continuously learn and apply best practices in data engineering and cloud computing. QUALIFICATIONS Proven experience as More ❯

associated roadmaps towards unlocking these in alignment with the analytics product development strategy and priorities. The role bridges str ategy, operations, and governance, focusing on enabling the organization to extract value from data while maintaining compliance and quality standards. What will be your Key Responsibilities? Strategic Data Management Execute the vision, strategy, and roadmap for the assigned data domain in … Qualifications Strong expertise in data management, data integration, and data engineering best practices. Proficiency in SQL, Python, or other data-focused programming languages. Experience with big data technologies and ETL processes. Project management skills with the ability to operate in Agile framework. Good communication skills, with a track record of aligning technical solutions to business needs. Knowledge of data governance More ❯

SQL and Apache Spark (Scala or Python). Relational Databases : Experience with on-premises and cloud-based SQL databases. Data Engineering Techniques : Skilled in Data Governance, Architecture, Data Modelling, ETL/ELT, Data Lakes, Data Warehousing, Master Data Management, and Business Intelligence. Engineering Delivery Practices : Solid understanding of Agile, DevOps, Git, APIs, Containers, Microservices, and Data Pipelines. Modern Data Tools More ❯

Technical Business Analysis experience. A proactive awareness of industry standards, regulations, and developments. Ideally, you'll also have: Experience of Relational Databases and Data Warehousing concepts. Experience of Enterprise ETL tools such as Informatica, Talend, Datastage or Alteryx. Project experience using the any of the following technologies: Hadoop, Spark, Scala, Oracle, Pega, Salesforce. Cross and multi-platform experience. Team building More ❯

and Databricks. Proficiency in working with the cloud environment and various platforms, including Azure, SQL Server. NoSQL databases is good to have. Hands-on experience with data pipeline development, ETL processes, and big data technologies (e.g., Hadoop, Spark, Kafka). Experience with DataOps practices and tools, including CI/CD for data pipelines. Experience in medallion data architecture and other More ❯

deliver measurable outcomes. Experience of working in environment where written and verbal communication are essential to delivery of outcomes. Desirable Awareness of data engineering concepts, including Data Warehousing or ETL processes. Exposure to deployment pipelines or CI/CD concepts, with a willingness to learn how code is tested and promoted into production environments. Familiarity with reporting and dashboarding tools More ❯

Azure Machine Learning Studio. Data Storage & Databases: SQL & NoSQL Databases: Experience with databases like PostgreSQL, MySQL, MongoDB, and Cassandra. Big Data Ecosystems: Hadoop, Spark, Hive, and HBase. Data Integration & ETL: Data Pipelining Tools: Apache NiFi, Apache Kafka, and Apache Flink. ETL Tools: AWS Glue, Azure Data Factory, Talend, and Apache Airflow. AI & Machine Learning: Frameworks: TensorFlow, PyTorch, Scikit-learn, Keras More ❯

with senior stakeholders. Architect & Build Scalable Data Solutions Collaborate closely with senior product stakeholders to understand data needs and architect end-to-end ingestion pipelines Design and build robust ETL/ELT processes and data architectures using modern tools and techniques Lead database design, data modelling, and integration strategies to support analytics at scale Drive Data Integration & Management Design and … of software engineering best practices - code reviews, testing frameworks, CI/CD, and code maintainability Experience deploying applications into production environments, including packaging, monitoring, and release management Ability to extract insights from complex and disparate data sets and communicate clearly with stakeholders Hands-on experience with cloud platforms such as AWS, Azure, or GCP Familiarity with traditional ETL tools (e.g. More ❯

intelligence solutions. Design, develop, and maintain BI solutions, including reports, dashboards, and data visualisations Collaborate with stakeholders to gather requirements and translate them into technical specifications Implement and optimise ETL processes to ensure efficient data integration from multiple sources Develop and maintain data models, ensuring data accuracy and consistency Create and maintain documentation for BI processes, data dictionaries, and user … in Computer Science, Information Systems, or a related field Minimum of 3 years' experience in BI development Strong proficiency in SQL and experience with data warehousing concepts Expertise in ETL processes and tools Proficient in using business intelligence tools such as Power BI, Tableau, or QlikView Solid understanding of data modelling techniques and best practices Experience with database management systems More ❯

and enhance report performance and usability. Automation and Workflow Management Use Power Automate to streamline data workflows and automate routine reporting tasks. Support cross-system data integration where applicable. ETL Development and Modernisation Build and maintain ETL pipelines using best practice methods and modern tooling. Support data transformation and movement across systems and platforms. Participate in the adoption and maintenance … T-SQL , including writing queries, procedures, and managing database structures. Proficient in Power BI dashboard development and DAX formulas. Experience with Power Automate for data-driven workflows. Understanding of ETL concepts and processes. Exposure to modern data platforms such as Azure Data Lake , Databricks , or Microsoft Fabric is a bonus. Analytical Skills: Ability to understand complex data structures and derive More ❯

Senior Data Engineer We are seeking a highly skilled Data Engineer to focus on maintaining data streams and ETL pipelines within a cloud-based environment. The ideal candidate will have experience in building, monitoring, and optimizing data pipelines, ensuring data consistency, and proactively collaborating with upstream and downstream teams to enable seamless data flow across the organization. In this role … between 25%-50% of the time per month at the client's office, which is located in London. Key Responsibilities: Data Pipeline Development & Maintenance Build, maintain, and optimize scalable ETL/ELT pipelines using tools such as Dagster, or similar. Ensure high data availability, reliability, and consistency through rigorous data validation and monitoring practices. Collaborate with cross-functional teams to More ❯

data and analytics needs. Design and deploy end-to-end data solutions using Microsoft Fabric, encompassing data ingestion, transformation, and visualisation workflows. Construct and refine data models, pipelines, and ETL frameworks within the Fabric ecosystem. Leverage Fabric's suite of tools to build dynamic reports, dashboards, and analytical applications. Maintain high standards of data integrity, consistency, and system performance across More ❯

Notebooks, Dataflows Gen2. Programming and query languages : Proficiency in Python, Apache Spark, KQL (Kusto Query Language). End-to-end data solution delivery : Experience with Data Governance, Migration, Modelling, ETL/ELT, Data Lakes, Warehousing, MDM, and BI. Engineering delivery practices : Knowledge of Agile, DevOps, Git, APIs, Containers, Microservices, and Data Pipeline orchestration. Broader platform experience (desirable): Familiarity with Databricks More ❯

intelligence and reporting tools like Tableau, PowerBI or similar. Experience with version control systems (e.g. Git) Ability to work in an Agile environment Experience with Microsoft SQL. Experience with ETL Tools and Data Migration. Experience with Data Analysis, Data mapping and UML. Experience with programming languages (Python, Ruby, C++, PHP, etc). The ability to work with large datasets across More ❯

intelligence and reporting tools like Tableau, PowerBI or similar. Experience with version control systems (e.g. Git) Ability to work in an Agile environment Experience with Microsoft SQL. Experience with ETL Tools and Data Migration. Experience with Data Analysis, Data mapping and UML. Experience with programming languages (Python, Ruby, C++, PHP, etc). The ability to work with large datasets across More ❯

intelligence and reporting tools like Tableau, PowerBI or similar. Experience with version control systems (e.g. Git) Ability to work in an Agile environment Experience with Microsoft SQL. Experience with ETL Tools and Data Migration. Experience with Data Analysis, Data mapping and UML. Experience with programming languages (Python, Ruby, C++, PHP, etc). The ability to work with large datasets across More ❯

usage of the new platform. Manage and mentor a team of data engineers, fostering a culture of technical excellence and collaboration. Define and enforce best practices in data modelling, ETL/ELT processes, and pipeline monitoring. Work closely with stakeholders across analytics, pricing, operations, finance, and product to understand their data needs and ensure the platform meets them. Manage project More ❯

data modeling, DAX, report design). Experience with Azure Data Factory and/or Microsoft Fabric for pipeline development (or python pipeline development) Understanding of data warehouse design and ETL/ELT best practices Strong communication and stakeholder engagement skills. Customer service mindset with integrity, professionalism and confidentiality. Self-motivated, diligent, and results oriented. Willingness to learn and grow in More ❯

decision making for our customers and partners. Position Responsibilities: Integrate various data sources and systems through a data pipeline into a data warehouse. Maintain and improve a data warehouse Extract, Transform, Load (ETL) and Datamart. Quickly become familiar with Boeing Global IT-related processes to enable implementation of requests and discovery of opportunities to automate or otherwise improve processes. Develop More ❯

using Azure Data Factory (ADF), ensuring efficient and reliable data movement and transformation. • Data Modelling using Kimball, 3NF or Dimensional methodologies • Utilize SQL and Python languages to extract, transform, and load data from various sources into Azure Databricks and Azure SQL/SQL Server. • Design and implement metadata driven pipelines to automate data processing tasks. • Collaborate with cross-functional teams More ❯