126 to 150 of 547 ETL Jobs in England

colleagues and stakeholders to ensure high-quality, maintainable, and scalable data solutions. Key Responsibilities Design and develop data processing software for deployment in Big Data technologies Build and maintain ETL/ELT pipelines using modern data platforms Collaborate with team members to resolve implementation challenges and ensure code quality Work with operations teams to ensure solutions are production-ready Contribute More ❯

Excellent communication and stakeholder management skills Flexible approach to hybrid working (attending workshops, possibly across differ locations if needed) Nice to have: Demonstrable background in Data Engineering Design processes (ETL, ELT), with good knowledge of Data Vault, Inmon and Kimball Insurance industry experience, with good understanding of what a claim is, claims process(es) etc Previous work on Data strategies More ❯

to detail, a high degree of intellectual curiosity, and the ability to manage multiple priorities. Advanced Excel skills, including pivot tables, formulas, and data modeling. Hands-on experience with ETL tools (e.g., Alteryx, KNIME, Tableau Prep). Intermediate to advanced proficiency in data visualization platforms such as Tableau, Power BI, QlikView, or Domo. Preferred Qualifications Experience in sales operations or More ❯

or GCP). Snowflake Expertise: Strong practical experience with Snowflake components (Snowpipe, Snowpark, Tasks, Dynamic Tables, UDFs). SnowPro certification preferred. Technical Proficiency: Advanced Python and SQL skills for ETL/ELT workflows and data transformations. Cloud & Automation: Familiarity with CI/CD pipelines and automated testing for data workflows. Governance & Security: Understanding of data governance frameworks and security best More ❯

or GCP). Snowflake Expertise: Strong practical experience with Snowflake components (Snowpipe, Snowpark, Tasks, Dynamic Tables, UDFs). SnowPro certification preferred. Technical Proficiency: Advanced Python and SQL skills for ETL/ELT workflows and data transformations. Cloud & Automation: Familiarity with CI/CD pipelines and automated testing for data workflows. Governance & Security: Understanding of data governance frameworks and security best More ❯

ll Bring Experience: Proven hands-on experience as a Data Engineer or in a similar data-focused role. Technical Skills: Proficiency in SQL and Python . Strong grasp of ETL/ELT pipelines , data modeling , and data warehousing . Experience with cloud platforms (AWS, Azure, GCP) and tools like Snowflake, Databricks, or BigQuery . Familiarity with streaming technologies (Kafka, Spark More ❯

or GCP). Snowflake Expertise: Strong practical experience with Snowflake components (Snowpipe, Snowpark, Tasks, Dynamic Tables, UDFs). SnowPro certification preferred. Technical Proficiency: Advanced Python and SQL skills for ETL/ELT workflows and data transformations. Cloud & Automation: Familiarity with CI/CD pipelines and automated testing for data workflows. Governance & Security: Understanding of data governance frameworks and security best More ❯

or GCP). Snowflake Expertise: Strong practical experience with Snowflake components (Snowpipe, Snowpark, Tasks, Dynamic Tables, UDFs). SnowPro certification preferred. Technical Proficiency: Advanced Python and SQL skills for ETL/ELT workflows and data transformations. Cloud & Automation: Familiarity with CI/CD pipelines and automated testing for data workflows. Governance & Security: Understanding of data governance frameworks and security best More ❯

or GCP). Snowflake Expertise: Strong practical experience with Snowflake components (Snowpipe, Snowpark, Tasks, Dynamic Tables, UDFs). SnowPro certification preferred. Technical Proficiency: Advanced Python and SQL skills for ETL/ELT workflows and data transformations. Cloud & Automation: Familiarity with CI/CD pipelines and automated testing for data workflows. Governance & Security: Understanding of data governance frameworks and security best More ❯

intelligent content governance, and personalized customer engagement. Drive seamless integration between CCM, ERP, CRM, ECM, and Power Platform ecosystems to enable a unified omnichannel experience. Oversee data lake architecture, ETL pipelines, and automation frameworks to accelerate digital transformation across centralized modules. Provide technical leadership and mentorship to architects, developers, and DevOps engineers; conduct architecture reviews, ensure HLD/LLD/ More ❯

learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience More ❯

learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience More ❯

learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience More ❯

learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience More ❯

learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience More ❯

Skills & Experience Strong experience in data architecture, ideally in customer-centric domains such as CRM, CDP, or marketing analytics. Strong knowledge of cloud platforms (Azure, GCP), data warehousing, and ETL tools. Proficiency in SQL, Python, and data modelling techniques. Experience with customer data platforms (e.g., Salesforce CDP, Redpoint), MDM, and real-time data processing. Understanding of data privacy, consent management More ❯

processes. What You'll Bring Technical Skills: Strong SQL expertise for querying, analysis, and troubleshooting within Snowflake. Hands-on experience with Snowflake environments & Source to Target Mapping Understanding of ETL/ELT processes to support data integration into Snowflake Workday & Salesforce Data Mappings and Migrations Business & Analytical Skills: Experience capturing and translating stakeholder requirements into actionable data specifications. Able to More ❯

Good SQL skills, you know your way around a database. Some exposure to a cloud-based data warehouse such as Snowflake, Redshift, Big Query or similar. Some knowledge of ETL/ELT and data automation. A desire to work with complex Salesforce detail and master that data. Excellent problem-solving skills and attention to detail. Strong communication and collaboration skills More ❯

resolve complex data issues and performance bottlenecks. Key Skills: SAS 9.4 (DI), SAS Viya 3.x (SAS Studio, VA, VI). Platform LSF, Jira, Platform Support. GIT. Strong expertise in ETL tools: Pentaho, Talend. Experience with data virtualization using Denodo. Proficiency in SAS for data analytics and reporting. Oracle (good to have). Solid understanding of Agile and Scrum frameworks. Hands More ❯

resolve complex data issues and performance bottlenecks. Key Skills: SAS 9.4 (DI), SAS Viya 3.x (SAS Studio, VA, VI). Platform LSF, Jira, Platform Support. GIT. Strong expertise in ETL tools: Pentaho, Talend. Experience with data virtualization using Denodo. Proficiency in SAS for data analytics and reporting. Oracle (good to have). Solid understanding of Agile and Scrum frameworks. Hands More ❯

seeking an Azure Data Engineer to help build and optimise data infrastructure on Microsoft Azure to support analytics, reporting, and secure data operations. Core Functions: * Develop scalable ELT/ETL pipelines using Azure tools (Data Factory, Synapse, Data Fabric) * Integrate data across systems (HR, CRM, legal, finance) * Enforce GDPR-compliant governance and security * Optimize performance and cost of data workflows More ❯

field or relevant industry industry experience Have knowledge of programming and data manipulation skills such as SQL and Python, and version control (Github) is essential Experience building multi-step ETL jobs/data pipelines and working with job scheduling systems is a plus Demonstrated ability to thrive with minimal oversight and process. You connect the dots across business needs and More ❯

Key skills: Strong experience with AWS data services (S3, Redshift, Glue, Lambda, Lake Formation, CloudFormation). Proficiency in SQL, Python (Pandas), Spark or Iceberg. Experience with data warehouse design, ETL/ELT, and CI/CD pipelines (GitHub, CodeBuild). Knowledge of infrastructure as code, performance tuning, and data migration. Exposure to DBT, Docker, or Microsoft BI stack is a More ❯

Key skills: Strong experience with AWS data services (S3, Redshift, Glue, Lambda, Lake Formation, CloudFormation). Proficiency in SQL, Python (Pandas), Spark or Iceberg. Experience with data warehouse design, ETL/ELT, and CI/CD pipelines (GitHub, CodeBuild). Knowledge of infrastructure as code, performance tuning, and data migration. Exposure to DBT, Docker, or Microsoft BI stack is a More ❯

accessibility through Python-based solutions. Key Requirements Strong programming skills in Python and JavaScript. Solid experience with SQL and database testing. Familiarity with data warehousing and ingestion (e.g., Snowflake, ETL/ELT). Proven ability to translate data into business insights. Clear communication skills for technical and non-technical audiences. Experience with data visualisation tools like Power BI or Tableau More ❯