1 to 25 of 57 Remote ETL Jobs in the South East

organisation to recruit a Junior Data Engineer. Hybrid working - London based Role The Junior Data Engineer will assist in the design, development, and maintenance of scalable data pipelines and ETL/ELT processes in Azure. Write efficient and reliable SQL queries for data extraction, transformation, and analysis. Support data integration from various sources (internal systems, third-party vendors) into centralised More ❯

discuss how your expertise could strengthen our growing data practice. As a data engineer/scientist, you will: Data Engineering Focus: Design, implement, and maintain scalable data pipelines and ETL processes Develop and maintain data warehouses and data lakes Implement data quality monitoring and validation systems Create and maintain data documentation and cataloguing systems Optimize data storage and retrieval systems More ❯

initiatives Ensure high standards of documentation and data security compliance Technical Skills (desirable): Microsoft Azure Data Services (e.g., Azure Data Factory, Synapse, Databricks, Fabric) Data warehousing and lakehouse design ETL/ELT pipelines SQL, Python for data manipulation and machine learning Big Data frameworks (e.g., Hadoop, Spark) Data visualisation (e.g., Power BI) Understanding of statistical analysis and predictive modelling Experience More ❯

initiatives Ensure high standards of documentation and data security compliance Technical Skills (desirable): Microsoft Azure Data Services (e.g., Azure Data Factory, Synapse, Databricks, Fabric) Data warehousing and lakehouse design ETL/ELT pipelines SQL, Python for data manipulation and machine learning Big Data frameworks (e.g., Hadoop, Spark) Data visualisation (e.g., Power BI) Understanding of statistical analysis and predictive modelling Experience 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 ❯

build and maintain scalable and secure data pipelines on the Azure platform. Develop and deploy data ingestion processes using Azure Data Factory, Databricks (PySpark), and Azure Synapse Analytics. Optimise ETL/ELT processes to improve performance, reliability and efficiency. Integrate multiple data sources including Azure Data Lake (Gen2), SQL-based systems and APIs. Collaborate with Data Architects, Analysts, and stakeholders More ❯

vibrant organisation. What You'll Do: Coding DAX Measures and Dimensional Models Developing & delivering visually compelling Power BI Dashboards & Reports to specification Developing and maintaining SSRS reports Developing & maintaining ETL pipeline solutions in Azure Data Factory and SSIS, utilising Azure Data Lake & Dev Ops Providing second & third line support for Data Team and own allocated support tickets Monitoring the Data More ❯

Fabric or strong expertise in related technologies such as Power BI, Azure Synapse, Data Factory, Azure Data Lake etc. A solid understanding of data engineering principles, including data modelling, ETL/ELT processes, and data warehousing. Hands-on experience with Power BI and DAX, and ideally some exposure to Notebooks, Pipelines, or Lakehouses within Fabric. Strong communication and stakeholder management More ❯

Relevant Microsoft certifications in Dynamics 365 and/or Power Platform. Experience working in agile delivery environments, particularly at scale. Knowledge of SSRS, FetchXML, SSIS, or other reporting and ETL tools. Experience with Power Pages (Portals) and customer-facing apps. Familiarity with data compliance standards (e.g., GDPR) and security models within Dynamics. Soft Skills & Traits A confident problem-solver with More ❯

Relevant Microsoft certifications in Dynamics 365 and/or Power Platform. Experience working in agile delivery environments, particularly at scale. Knowledge of SSRS, FetchXML, SSIS, or other reporting and ETL tools. Experience with Power Pages (Portals) and customer-facing apps. Familiarity with data compliance standards (e.g., GDPR) and security models within Dynamics. Soft Skills & Traits A confident problem-solver with More ❯

patterns, and data quality issues. Collaborate with cross-functional teams to define data needs and deliver insights. Build dashboards and reports using tools like Power BI or Tableau. Support ETL workflows and contribute to data pipeline development. Ensure accuracy and consistency of data throughout transformation. Present findings clearly to both technical and non-technical stakeholders. Play a key role in More ❯

data warehouses and ensuring data quality on GCP Strong hands-on experience with BigQuery, Dataproc, Dataform, Composer, Pub/Sub Skilled in PySpark, Python and SQL Solid understanding of ETL/ELT processes Clear communication skills and ability to document processes effectively Desirable Skills: GCP Professional Data Engineer certification Exposure to Agentic AI systems or intelligent/autonomous data workflows More ❯

BI dashboards and reports to deliver key financial and operational insights. Connecting to various data sources (e.g., SQL databases, Excel, financial systems) and performing data extraction, transformation, and loading (ETL) processes within Power BI (using Power Query/M language). Collaborating with stakeholders to gather requirements, understand business needs, and translate them into effective Power BI solutions. Be able More ❯

BI dashboards and reports to deliver key financial and operational insights. Connecting to various data sources (e.g., SQL databases, Excel, financial systems) and performing data extraction, transformation, and loading (ETL) processes within Power BI (using Power Query/M language). Collaborating with stakeholders to gather requirements, understand business needs, and translate them into effective Power BI solutions. Be able More ❯

Profile Data Engineer - Surrey - Hybrid A successful Data Engineer should have: Experience with Azure Data Factory, Azure Synapse, Azure SQL, or Azure Data Lake. Hands-on knowledge of the ETL process and working with large datasets. Understanding of dimensional modelling and data warehousing principles. Familiarity with CI/CD pipelines or monitoring tools for data processes. Solid skills in SQL More ❯

Fabric or strong expertise in related technologies such as Power BI, Azure Synapse, Data Factory, Azure Data Lake etc. A solid understanding of data engineering principles, including data modelling, ETL/ELT processes, and data warehousing. Hands-on experience with Power BI and DAX, and ideally some exposure to Notebooks, Pipelines, or Lakehouses within Fabric. Strong communication and stakeholder management More ❯

detailed management reports. Strong analytical background, including Excel, MS Access, SQL, Power BI, ArcGIS Online, and FME. Knowledge and capability in a wide variety of additional analytical tools and ETL (e.g. Python, SQL, Databricks, Microsoft Flow, Azure Data Factory). Degree in Environmental Science, Data Management, Hydrology, or a related field. Experience with remote sensing technologies and water quality monitoring More ❯

within Power BI Support the integration and management of Microsoft Fabric as part of the evolving data architecture Participate in the full project lifecycle from design to deployment Optimise ETL/ELT processes and propose enhancements to existing systems Implement and maintain API integrations Collaborate with users, analysts, and developers to drive data performance improvements Document data models, pipelines, and … similar technical role Hands-on experience with key Microsoft Azure services: Azure Data Factory Azure Synapse Analytics Azure Data Lake Storage Azure SQL Database Solid understanding of data modeling, ETL/ELT, and warehousing concepts Proficiency in SQL and one or more programming languages (e.g., Python, Scala) Exposure to Microsoft Fabric, or a strong willingness to learn Experience using version More ❯

lifecycle processes and optimise cloud resource usage Support analytics and self-service reporting initiatives Skills & Experience Strong experience with GCP, BigQuery, Dataflow Proficiency in Python and Terraform Skilled in ETL/ELT, data modelling, and metadata management Familiarity with CI/CD, DevOps, and Infrastructure-as-Code Knowledge of insurance data and KPIs is advantageous but not essential Benefits: Competitive More ❯

understanding of query optimisation and performance tuning. Strong understanding of data warehousing concepts and dimensional data modelling. Experience integrating OBIEE with Oracle and non-Oracle data sources. Familiarity with ETL processes and tools (e.g., ODI, Informatica) is a plus. Experience with Oracle BI Publisher is a bonus. Excellent analytical, problem-solving, and communication skills. Company Market leading financial services organisation More ❯

and upskill the function Leading and executing a data platform migration into Google Cloud Platform (GCP) -initially in partnership with a consultancy Owning all aspects of the data warehouse, ETL/ELT, and platform infrastructure (DevOps, FinOps) Driving forward best practices in data governance, access control, and architecture Collaborating cross-functionally with pricing, analytics, IT, and commercial teams Helping shape More ❯

field and/or statistical background. Technical requirements: Proficient in SQL?and hands-on coding experience with Python for Data Analytics Experience with setting up and automating data pipelines, ETL processes, etc Proficiency in using data visualization tools such as PowerBI or Tableau In-depth experience with Adobe Analytics or Google Analytics Expert at designing, running and interpreting AB tests. More ❯

tuning models in production Advanced proficiency in Python for data analysis, machine learning, and production-ready pipelines Solid experience with SQL for data manipulation Deep understanding of data modelling, ETL processes, and relational databases Experience with big data technologies and cloud platforms, ideally Azure Exposure to embedding models, vector search, and scalable deployment of LLM-powered solutions Other information Company More ❯

tuning models in production Advanced proficiency in Python for data analysis, machine learning, and production-ready pipelines Solid experience with SQL for data manipulation Deep understanding of data modelling, ETL processes, and relational databases Experience with big data technologies and cloud platforms, ideally Azure Exposure to embedding models, vector search, and scalable deployment of LLM-powered solutions Other information Company More ❯

data architecture principles, including data modelling, database design, data management, and data governance You are proficient in data technologies such as SQL, NoSQL, graph databases, data lakes, data mesh, ETL processes, data platforms, and data warehousing You possess excellent analytical skills to evaluate, integrate, and optimize data systems and solutions You have a forward-thinking approach to data architecture, incorporating More ❯