1 to 25 of 301 Remote ETL Jobs in England

from the warehouse. Maintaining and improving the existing Python-based dynamic pricing model and web scraping tools. 🎯 What we’re looking for: Experience across a modern data stack for ETL/ELT processes and data warehousing. Strong SQL and Python skills, with an understanding of Kimball-style data modelling . Experience with DBT, Dagster, or Airflow for transformation and orchestration. More ❯

from the warehouse. Maintaining and improving the existing Python-based dynamic pricing model and web scraping tools. What we're looking for: Experience across a modern data stack for ETL/ELT processes and data warehousing. Strong SQL and Python skills, with an understanding of Kimball-style data modelling . Experience with DBT, Dagster, or Airflow for transformation and orchestration. More ❯

and shape the direction of the platform as it evolves, pushing the boundaries of what’s possible with data and AI. What You’ll Do Design & build high-performance ETL/ELT pipelines in modern cloud environments (including Azure, AWS, GCP, Snowflake or Databricks). Lead CI/CD automation, environment versioning, and production deployments for data products. Integrate AI More ❯

and shape the direction of the platform as it evolves, pushing the boundaries of what’s possible with data and AI. What You’ll Do Design & build high-performance ETL/ELT pipelines in modern cloud environments (including Azure, AWS, GCP, Snowflake or Databricks). Lead CI/CD automation, environment versioning, and production deployments for data products. Integrate AI More ❯

and shape the direction of the platform as it evolves, pushing the boundaries of what's possible with data and AI. What You'll Do Design & build high-performance ETL/ELT pipelines in modern cloud environments (including Azure, AWS, GCP, Snowflake or Databricks). Lead CI/CD automation, environment versioning, and production deployments for data products. Integrate AI More ❯

This role has a direct opportunity to grow into a Head of Data and AI position. Key Responsibilities Data Engineering & Architecture Lead the development and maintenance of data pipelines, ETL processes, and warehouse architecture (GCP, Azure). Ensure high-quality, scalable, and secure data infrastructure that supports campaign reporting and advanced analytics. Design and support the delivery of AI and More ❯

of views/tables, functions and stored procedures. Experience in gathering BI requirements and understand the business on different levels. Experience in developing new or maintaining and improving existing ETL processes. Experience in establishing and maintaining collaborative relationships with stakeholders. Understanding dimensional modelling ideally for Public Sector Good communications, interpersonal and presentation skills in order to influence internal stakeholders. Ability More ❯

WFHDuration: 3 months rolling contractType of contract : Freelance, Inside IR35Level: mid-Senior Duties and Tasks: Develop and optimize data pipelines using Databricks and Spark.Design and implement data models and ETL processes in Snowflake.Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.Ensure data quality, integrity, and security across platforms.Monitor and troubleshoot data workflows and performance issues. Requirements: Proven More ❯

staff. Required Skills & Qualifications: Experience designing cloud data platforms in Azure/AWS or significant on-premise design experience. 5+ years in data engineering or business intelligence roles. Extensive ETL and data pipeline design experience, technology agnostic. Proficiency in SQL and experience with data engineering coding languages such as Python, R, or Spark. Understanding of data warehouse and data lake More ❯

and lakehouses using Databricks , with additional exposure to Snowflake, Azure Synapse, or Fabric being a bonus. Data Modelling – Build and optimise enterprise-grade data models across varied data layers. ETL/ELT Engineering – Use tooling such as Databricks, SSIS, ADF, Informatica, IBM DataStage to drive efficient data ingestion and transformation. Data Governance – Implement governance and MDM using tools like Unity More ❯

and lakehouses using Databricks , with additional exposure to Snowflake, Azure Synapse, or Fabric being a bonus. Data Modelling – Build and optimise enterprise-grade data models across varied data layers. ETL/ELT Engineering – Use tooling such as Databricks, SSIS, ADF, Informatica, IBM DataStage to drive efficient data ingestion and transformation. Data Governance – Implement governance and MDM using tools like Unity More ❯

scientists, analysts, and software engineers to ensure the company's data strategy underpins their innovative financial products. Key Responsibilities: Lead the design, development, and optimisation of data pipelines and ETL processes. Architect scalable data solutions to support analytics, machine learning, and real-time financial applications. Drive best practices for data engineering, ensuring high levels of data quality, governance, and security. More ❯

scientists, analysts, and software engineers to ensure the company's data strategy underpins their innovative financial products. Key Responsibilities: Lead the design, development, and optimisation of data pipelines and ETL processes. Architect scalable data solutions to support analytics, machine learning, and real-time financial applications. Drive best practices for data engineering, ensuring high levels of data quality, governance, and security. More ❯

Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns, ETL/ELT, and data pipeline orchestration Experience with data quality frameworks, metadata management, and data lineage Hands-on experience with machine learning pipelines and generative AI engineering Familiarity with DevOps More ❯

Apache Spark Proven experience in Snowflake data engineering, including: Snowflake SQL, Snowpipe, Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns, ETL/ELT, and data pipeline orchestration Experience with data quality frameworks, metadata management, and data lineage Hands-on experience with machine learning pipelines and generative AI engineering Familiarity with DevOps More ❯

making. In this role, you will be responsible for: Building and managing data pipelines using Azure Data Factory and related services. Building and maintaining data lakes, data warehouses, and ETL/ELT processes. Designing scalable data solutions and models for reporting in Power BI. Supporting data migration from legacy systems into the new platform. Ensuring data models are optimised for More ❯

making. In this role, you will be responsible for: Building and managing data pipelines using Azure Data Factory and related services. Building and maintaining data lakes, data warehouses, and ETL/ELT processes. Designing scalable data solutions and models for reporting in Power BI. Supporting data migration from legacy systems into the new platform. Ensuring data models are optimised for More ❯

making. In this role, you will be responsible for: Building and managing data pipelines using Azure Data Factory and related services. Building and maintaining data lakes, data warehouses, and ETL/ELT processes. Designing scalable data solutions and models for reporting in Power BI. Supporting data migration from legacy systems into the new platform. Ensuring data models are optimised for More ❯

internal best practices What You’ll Bring: Strong experience in data engineering with Microsoft Fabric Solid understanding of DataOps, CI/CD, and automation Hands-on experience with Jira, ETL/ELT, and data modelling Familiarity with Power BI, DAX, or Azure DevOps Excellent communication and stakeholder engagement skills Consulting or client-facing experience is a plus 🌱 Career Progression: Clear More ❯

internal best practices What You’ll Bring: Strong experience in data engineering with Microsoft Fabric Solid understanding of DataOps, CI/CD, and automation Hands-on experience with Jira, ETL/ELT, and data modelling Familiarity with Power BI, DAX, or Azure DevOps Excellent communication and stakeholder engagement skills Consulting or client-facing experience is a plus 🌱 Career Progression: Clear More ❯

Data Factory, Lakehouse, Power BI) Strong proficiency in SQL, DAX, and Power Query (M) Experience with Azure Data Services (Synapse, Data Lake, Azure SQL) Solid understanding of data modelling, ETL processes, and BI architecture Familiarity with CI/CD pipelines, DevOps, and version control (Git) Excellent communication and stakeholder management skills Ability to work independently and lead technical delivery Desirable More ❯

Data Factory, Lakehouse, Power BI) Strong proficiency in SQL, DAX, and Power Query (M) Experience with Azure Data Services (Synapse, Data Lake, Azure SQL) Solid understanding of data modelling, ETL processes, and BI architecture Familiarity with CI/CD pipelines, DevOps, and version control (Git) Excellent communication and stakeholder management skills Ability to work independently and lead technical delivery Desirable More ❯

data modellers, and reporting teams to ensure the curated data supports deeper insights into corporate performance Optimise data pipelines for scalability, reliability, and maintainability using best practices (e.g., modular ETL design, version control, CI/CD) Strong understanding of Microsoft Fabric architecture and components Expertise in Microsoft Fabric Data Engineering Fabric Dataflows/Azure Data Factory Experience with Azure Synapse More ❯

Extensive experience in designing cloud data platforms using Azure, AWS, or exceptional on-premise design expertise. At least 5 years in data engineering or business intelligence roles. Proficiency in ETL and data pipeline design, with a technology-agnostic approach. A solid understanding of data warehouse and data lake principles. Expert SQL skills and demonstrable data modelling capabilities. About the Company More ❯

Extensive experience in designing cloud data platforms using Azure, AWS, or exceptional on-premise design expertise. At least 5 years in data engineering or business intelligence roles. Proficiency in ETL and data pipeline design, with a technology-agnostic approach. A solid understanding of data warehouse and data lake principles. Expert SQL skills and demonstrable data modelling capabilities. About the Company More ❯