1 to 25 of 75 Remote ETL Jobs in London

seamlessly across data, commercial, and ops teams. Hard Skills Required Programming & Data Science: Python (Pandas, NumPy, scikit-learn, TensorFlow or PyTorch) essential; R (desirable) Data Engineering & Cloud: Advanced SQL, ETL/ELT tools (Airflow/dbt), AWS/Azure/GCP Machine Learning & AI: Classification, regression, clustering, forecasting; NLP (text mining, sentiment, LLM fine-tuning); GenAI frameworks Analytics & Visualisation: BI More ❯

DevOps, and GitHub. Data Modelling Apply hands-on expertise in enterprise data modelling using tools such as ERwin, ER/Studio, or PowerDesigner to ensure performance, scalability, and maintainability. ETL/ELT Frameworks Design robust data pipelines using tools like Cloud Composer, Dataflow, Dataproc, Informatica, or IBM DataStage, supporting both batch and streaming ingestion. Data Governance & Quality Implement governance frameworks More ❯

DevOps, and GitHub. Data Modelling Apply hands-on expertise in enterprise data modelling using tools such as ERwin, ER/Studio, or PowerDesigner to ensure performance, scalability, and maintainability. ETL/ELT Frameworks Design robust data pipelines using tools like Cloud Composer, Dataflow, Dataproc, Informatica, or IBM DataStage, supporting both batch and streaming ingestion. Data Governance & Quality Implement governance frameworks More ❯

Experience with Tableau, Alteryx, Tableau Prep. Hands-on experience with SAP SuccessFactors, SAP Analytics Cloud (SAC). Knowledge of data visualisation best practices and dashboard design principles. Experience with ETL processes and data transformation workflows. Understanding of HR data structures, key metrics, and reporting requirements. Experience supporting HR system migrations or implementations. Experience supporting technology implementations or large-scale transformation More ❯

background in data analysis, cleansing, enrichment, metadata management, and data innovation. Proficiency in SQL and MySQL. Experience with business intelligence tools: Power BI, Sisense, Quicksight. Hands-on experience with ETL tools, ideally Sagemaker Unified Studio. Ability to validate, test, and build data engineering solutions. Strong communication skills with ability to translate between technical and non-technical stakeholders. Desirable More ❯

background in data analysis, cleansing, enrichment, metadata management, and data innovation. Proficiency in SQL and MySQL. Experience with business intelligence tools: Power BI, Sisense, Quicksight. Hands-on experience with ETL tools, ideally Sagemaker Unified Studio. Ability to validate, test, and build data engineering solutions. Strong communication skills with ability to translate between technical and non-technical stakeholders. Desirable More ❯

focus on Snowflake and Power BI. Strong expertise in data modelling, query optimisation, and Power BI development (DAX, dashboards). Hands-on with dbt, SQL, Python, and ELT/ETL pipeline development. Experience with Azure Data Factory (ADF), and migrating legacy data platforms to cloud solutions. Financial services exposure, ideally with market or credit risk analytics. Ability to produce technical More ❯

building and guiding high-performing engineering teams • Strong hands-on expertise in cloud platforms (GCP, AWS, or Azure) with emphasis on cloud-native architectures • Deep understanding of data engineering - ETL/ELT, real-time/batch processing, data lakes/warehouses, and data governance • Track record of delivering complex, scalable systems that drive measurable business impact • Strong software engineering foundation 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 ❯

decisions and shape the company's long-term data strategy. What you'll be doing: Designing, developing, and owning scalable data pipelines and APIs . Building infrastructure for optimal ETL/ELT processes across diverse data sources. Working with Azure, dbt, SQL, and Python to deliver cloud-first solutions. Taking ownership of data quality and identifying opportunities for continuous improvement. More ❯

is passionate about data, cloud technologies, and scalable systems, and wants to have a direct impact on data-driven decision-making. Key Responsibilities: Design, build, and maintain scalable and reliable ETL/ELT data pipelines using Python, PySpark, and SQL. Develop and manage data workflows and orchestration using tools such as Airflow or similar. Optimize data processes for performance, scalability … transformation, Data domain knowledge, Data Integration, Data Management, Data Manipulation, Data Sourcing, Data strategy and governance, Data Structures and Algorithms (Inactive), Data visualization and interpretation, Digital Security, Extract, transform and load, Group Problem Solving Legal Disclaimer: We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national More ❯

of experience in data engineering (healthcare/medical devices preferred but not required) Strong Python programming and data engineering skills (Pandas, PySpark, Dask) Proficiency with databases (SQL/NoSQL), ETL processes, and modern data frameworks (Apache Spark, Airflow, Kafka) Solid experience with cloud platforms (AWS, GCP, or Azure) and CI/CD for data pipelines Understanding of data privacy and More ❯

and presentation skills. Preferred Skills Knowledge of FP&A, supply chain, workforce, or sales planning processes. Experience with data visualization tools (Power BI, Tableau, or similar). Familiarity with ETL tools, APIs, or middleware for system integrations. Anaplan Solution Architect certification (a plus for senior roles). More ❯

Key Requirements: Proven expertise in Data Solution Architecture working on large, complex Data Programmes Strong Data Modelling experience (especially Conceptual Data Models) Demonstrable background in Data Engineering Design processes (ETL, ELT), with good knowledge of Data Vault, Inmon and Kimball Strong knowledge of MS Azure stack (including Data Factory (ADF), Data Lake Storage, SQL, Azure ML and Power BI) Proven More ❯

Microsoft Azure Data Services (Fabric desirable). Knowledge of Data Lake, Power BI, SQL. Business Entity Mastering, Data Taxonomy and Data Dictionary. Knowledge of CI/CD Familiarity with ETL processes and best practices. Key Competencies Motivated to learn and grow in a dynamic environment. Strong organisational and technical skills with excellent attention to detail. Resilient, solution-focused, and able More ❯

Microsoft Azure Data Services (Fabric desirable). Knowledge of Data Lake, Power BI, SQL. Business Entity Mastering, Data Taxonomy and Data Dictionary. Knowledge of CI/CD Familiarity with ETL processes and best practices. Key Competencies Motivated to learn and grow in a dynamic environment. Strong organisational and technical skills with excellent attention to detail. Resilient, solution-focused, and able More ❯

data flows, mappings, and processes. What You'll Bring Technical Skills: Strong SQL expertise for querying, analysis, and troubleshooting within Snowflake. Hands-on experience with Snowflake environments Understanding of ETL/ELT processes to support data integration into Snowflake. Business & Analytical Skills: Experience capturing and translating stakeholder requirements into actionable data specifications. Analytical mindset with attention to detail and a 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 ❯

and maintenance of our data infrastructure, driving our large-scale programmes in the USA. Your primary responsibilities will include : Design & Development: Create, develop, and maintain scalable data pipelines and ETL processes across various systems. Data Integration: Build and manage seamless data integrations from diverse sources, including POS systems, e-commerce platforms, RFID sensors, IoT devices, and CRM systems. Data optimisation More ❯

and maintenance of our data infrastructure, driving our large-scale programmes in the USA. Your primary responsibilities will include : Design & Development: Create, develop, and maintain scalable data pipelines and ETL processes across various systems. Data Integration: Build and manage seamless data integrations from diverse sources, including POS systems, e-commerce platforms, RFID sensors, IoT devices, and CRM systems. Data optimisation More ❯

management, incentive compensation, deal desk, lead management, and contact centre operations . Use SQL and Python (Pandas, PySpark) to analyse data, automate workflows, and generate insights. Design and manage ETL/ELT processes, data models, and reporting automation . Leverage Databricks, Snowflake, and GCP to enable scalable reporting and analytics. Partner with leadership to identify opportunities for new tools, automation More ❯

innovation. What you'll be doing: Designing and building scalable data pipelines to support analytics, reporting, and machine learning. Leading the implementation of Azure data solutions and ensuring robust ETL/ELT processes. Defining architecture strategies that allow for scalable, flexible development. Embedding best practices in DevOps, CI/CD, and engineering standards . Mentoring and growing a high-performing More ❯

Requirements Proficiency in Python, with a focus on clean, maintainable code (bonus for experience with type hints, linters, and testing frameworks like pytest) Solid understanding of data engineering fundamentals: ETL/ELT, schema evolution, batch processing Experience or strong interest in Apache Spark for distributed data processing Familiarity with AWS data tools (e.g., S3, Glue, Lambda, EMR) Strong communication skills More ❯

Requirements Proficiency in Python, with a focus on clean, maintainable code (bonus for experience with type hints, linters, and testing frameworks like pytest) Solid understanding of data engineering fundamentals: ETL/ELT, schema evolution, batch processing Experience or strong interest in Apache Spark for distributed data processing Familiarity with AWS data tools (e.g., S3, Glue, Lambda, EMR) Strong communication skills More ❯