1 to 25 of 113 ETL Jobs in Central London

Exp: 10 + yrs Job Summary The Senior Test Specialist/Architect in Cloud Automation Testing focuses on automating testing processes in ETL (Extract, Transform, Load) and Data Warehousing environments to ensure the quality and reliability of data pipelines. The role involves designing, developing, and implementing automation scripts for testing data transformations, data loading processes, and data quality verification. Key … Responsibilities 1. Develop and execute automated test scripts for etl processes and data pipelines. 2. Collaborate with cross functional teams to design and implement automated testing frameworks. 3. Create test plans and test cases for etl and data warehouse testing. 4. Identify and troubleshoot issues in data transformations and data loading processes. 5. Conduct performance testing and ensure scalability of … data pipelines. 6. Implement best practices for data quality assurance in etl environments. Skill Requirements 1. Proficiency in cloud-based automation testing tools like selenium, appium, or similar. 2. Experience in automation testing of etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as More ❯

Exp: 10 + yrs Job Summary The Senior Test Specialist/Architect in Cloud Automation Testing focuses on automating testing processes in ETL (Extract, Transform, Load) and Data Warehousing environments to ensure the quality and reliability of data pipelines. The role involves designing, developing, and implementing automation scripts for testing data transformations, data loading processes, and data quality verification. Key … Responsibilities 1. Develop and execute automated test scripts for etl processes and data pipelines. 2. Collaborate with cross functional teams to design and implement automated testing frameworks. 3. Create test plans and test cases for etl and data warehouse testing. 4. Identify and troubleshoot issues in data transformations and data loading processes. 5. Conduct performance testing and ensure scalability of … data pipelines. 6. Implement best practices for data quality assurance in etl environments. Skill Requirements 1. Proficiency in cloud-based automation testing tools like selenium, appium, or similar. 2. Experience in automation testing of etl (extract, transform, load) processes and data warehousing. 3. Strong understanding of sql for data querying and validation. 4. Knowledge of big data technologies such as More ❯

architectures that drive measurable transformation aligned to banking sector priorities. Client Advisory & Engagement – Act as a trusted advisor, leading workshops and influencing senior stakeholders on strategy, roadmaps, and innovation. ETL/ELT & Data Engineering – Provide oversight on robust data pipeline and integration designs using SSIS, ADF, Informatica, or IBM DataStage. Data Governance & Quality – Define governance, metadata, and quality frameworks using 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 ❯

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 ❯

suited to someone who's confident communicating with data, product, and engineering teams, not a 'heads-down coder' type. Top 4 Core Skills Python - workflow automation, data processing, and ETL/ELT development. Snowflake - scalable data architecture, performance optimisation, and governance. SQL - expert-level query writing and optimisation for analytics and transformations. dbt (Data Build Tool) - modular data modelling, testing More ❯

Dimensional modelling (star schema, snowflake, denormalised structures, SCD handling) DAX, Visual Studio and data transformation logic Azure Fabric, Azure Data Factory, Synapse, Data Lakes and Lakehouse/Warehouse technologies ETL/ELT orchestration for structured and unstructured data Proficiency in: PySpark, T-SQL, Notebooks and advanced data manipulation Performance monitoring and orchestration of Fabric solutions Power BI semantic models and More ❯

Dimensional modelling (star schema, snowflake, denormalised structures, SCD handling) DAX, Visual Studio and data transformation logic Azure Fabric, Azure Data Factory, Synapse, Data Lakes and Lakehouse/Warehouse technologies ETL/ELT orchestration for structured and unstructured data Proficiency in: PySpark, T-SQL, Notebooks and advanced data manipulation Performance monitoring and orchestration of Fabric solutions Power BI semantic models and 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 ❯

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 ❯

solution design on GCP, BigQuery, Databricks, Snowflake Drive cloud migration & modernisation strategies (Terraform, CI/CD, Azure DevOps, GitHub) Define enterprise data models (ERwin, ER/Studio, PowerDesigner) Architect ETL/ELT frameworks & pipelines (Dataflow, Dataproc, Informatica, etc.) Implement governance & quality frameworks (Unity Catalog, Profisee, Alation, DQ Pro) Engage clients at C-suite level to shape roadmaps & business cases Mentor More ❯

Build sophisticated reporting solutions and drive the adoption of generative AI to enable intuitive self-service analytics. Enhance data engineering processes through automation, CI/CD pipelines and optimized ETL/ELT workflows. Experiment with new tools, technologies and approaches to support the organisation’s analytics and insights strategy. Provide ongoing support for data products, including incident management and defining More ❯

Build sophisticated reporting solutions and drive the adoption of generative AI to enable intuitive self-service analytics. Enhance data engineering processes through automation, CI/CD pipelines and optimized ETL/ELT workflows. Experiment with new tools, technologies and approaches to support the organisation’s analytics and insights strategy. Provide ongoing support for data products, including incident management and defining 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 ❯

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 ❯

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 ❯

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 ❯

native Azure services Requirements: 10+ years in cloud architecture/engineering with a strong focus on building scalable data pipelines Expertise in Azure Databricks (7+years) including building and managing ETL pipelines using PySpark or Scala (essential) Solid understanding of Apache Spark, Delta Lake, and distributed data processing concepts Hands-on experience with Azure Data Lake Storage Gen2, Azure Data Factory More ❯

Domain is a must. Under 7 years of experience only. Permanent. Key Responsibilities Design, develop, and maintain data ingestion pipelines using open-source frameworks and tools Build and optimise ETL/ELT processes to handle small to large-scale data processing requirements Develop data models and schemas that support analytics, business intelligence and product needs Monitor, troubleshoot, and optimise data More ❯

at least one of: Front Office (Sales & Trading), Risk Management, or Finance. Strong programming in Python, Java and SQL (Rust a plus). Proven experience building streaming and batch ETL/ELT pipelines at scale. Strong understanding of market/trade data lifecycles and time series concepts. Experience with AWS and cloud-native data services. Excellent communication and stakeholder management More ❯

Domain is a must. Under 7 years of experience only. Permanent. Key Responsibilities Design, develop, and maintain data ingestion pipelines using open-source frameworks and tools Build and optimise ETL/ELT processes to handle small to large-scale data processing requirements Develop data models and schemas that support analytics, business intelligence and product needs Monitor, troubleshoot, and optimise data More ❯

at least one of: Front Office (Sales & Trading), Risk Management, or Finance. Strong programming in Python, Java and SQL (Rust a plus). Proven experience building streaming and batch ETL/ELT pipelines at scale. Strong understanding of market/trade data lifecycles and time series concepts. Experience with AWS and cloud-native data services. Excellent communication and stakeholder management More ❯

DevOps team to deliver data solutions and maintain live systems. Apply best practices for data integration, transformation, and delivery in a secure and scalable environment. Support data pipelines and ETL processes across various technologies and cloud platforms Maintain, monitor, and troubleshoot systems using a wide array of tools and platforms. Contribute to automation and continuous integration/deployment (CI/ More ❯