1 to 25 of 279 Remote ETL Jobs

Embedded Analytics, and S/4HANA business processes. Proficiency in frontend tools such as Power BI, Tableau, or similar platforms. Strong understanding of data warehousing concepts, data modelling, and ETL processes. Strong understanding of SAP Datasphere and basic knowledge of SAP Business data cloud and Azure Databricks Excellent analytical and problem-solving skills, with the ability to work with complex 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

s or Master’s degree in Computer Science, Mathematics, or related field. Proven experience leading and scaling high-performing data engineering teams. Strong knowledge of Azure Data Stack, Databricks, ETL/ELT pipelines, and data warehousing. Expertise in database architecture, SQL, and data modeling. Experience with enterprise platforms such as Salesforce or SAP. Agile or iterative project management experience. Excellent 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 ❯

modernisation of the data estate, migrating legacy SQL Server warehouses into Azure. You will play a key role in shaping the new cloud data platform. Responsibilities: Build and optimise ETL/ELT pipelines with Azure Data Factory, Synapse, and SQL Database. Lead the migration of on-premises SQL Server/SSIS workloads into Azure. Design data lakes, marts, and models More ❯

You'll Be Doing Delivering full lifecycle data solutions: acquisition, engineering, modelling, analysis, and visualisation Leading client workshops and translating business needs into technical solutions Designing and implementing scalable ETL/ELT pipelines using Azure tools (Fabric, Databricks, Synapse, Data Factory) Building data lakes with medallion architecture Migrating legacy on-prem data systems to the cloud Creating impactful dashboards and More ❯

You'll Be Doing Delivering full lifecycle data solutions: acquisition, engineering, modelling, analysis, and visualisation Leading client workshops and translating business needs into technical solutions Designing and implementing scalable ETL/ELT pipelines using Azure tools (Fabric, Databricks, Synapse, Data Factory) Building data lakes with medallion architecture Migrating legacy on-prem data systems to the cloud Creating impactful dashboards and More ❯

You'll Be Doing Delivering full lifecycle data solutions: acquisition, engineering, modelling, analysis, and visualisation Leading client workshops and translating business needs into technical solutions Designing and implementing scalable ETL/ELT pipelines using Azure tools (Fabric, Databricks, Synapse, Data Factory) Building data lakes with medallion architecture Migrating legacy on-prem data systems to the cloud Creating impactful dashboards and More ❯

You'll Be Doing Delivering full lifecycle data solutions: acquisition, engineering, modelling, analysis, and visualisation Leading client workshops and translating business needs into technical solutions Designing and implementing scalable ETL/ELT pipelines using Azure tools (Fabric, Databricks, Synapse, Data Factory) Building data lakes with medallion architecture Migrating legacy on-prem data systems to the cloud Creating impactful dashboards and More ❯

You'll Be Doing Delivering full lifecycle data solutions: acquisition, engineering, modelling, analysis, and visualisation Leading client workshops and translating business needs into technical solutions Designing and implementing scalable ETL/ELT pipelines using Azure tools (Fabric, Databricks, Synapse, Data Factory) Building data lakes with medallion architecture Migrating legacy on-prem data systems to the cloud Creating impactful dashboards and More ❯

You'll Be Doing Delivering full lifecycle data solutions: acquisition, engineering, modelling, analysis, and visualisation Leading client workshops and translating business needs into technical solutions Designing and implementing scalable ETL/ELT pipelines using Azure tools (Fabric, Databricks, Synapse, Data Factory) Building data lakes with medallion architecture Migrating legacy on-prem data systems to the cloud Creating impactful dashboards and 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 ❯

management position. Financial services experience is essential , ideally covering lending, servicing, or securitisation data. Deep technical expertise in Microsoft and Azure data technologies. Strong knowledge of data modelling (Kimball) , ETL/ELT , and hybrid cloud architectures . Proven ability to drive quality, governance, and best practices within engineering teams. Excellent communication, stakeholder management, and leadership skills. If you're interested More ❯

end-to-end data solutions, including acquisition, engineering, modelling, analysis, and visualisation. Lead client workshops to gather requirements and communicate effectively across technical and business stakeholders. Design and implement ETL/ELT pipelines using Microsoft Fabric, Azure Synapse, or Databricks - experience with at least one of these platforms is essential. Build scalable data lake solutions using medallion architecture principles. Migrate More ❯

supporting documents. Person Specification Experience Essential MS SQL Server - development Design and implementation of complex data models used for Business Intelligence and Advanced Analytics Design and implementation of complex ETL/ELT processes used for Business Intelligence and Advanced Analytics Experience in a supervisory role In-depth knowledge of NHS data and issues Visualization and report writing skills Significant experience 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 ❯

and optimising data pipelines (batch and streaming) and integrating cloud-based platforms (e.g., Azure Synapse, AWS Redshift, Google BigQuery ) with legacy systems, ensuring performance and scalability. Deep knowledge of ETL/ELT processes , leveraging tools like Apache Airflow, dbt, or Informatica , with a focus on ensuring data quality, lineage, and integrity across the data lifecycle. Practical expertise in data and More ❯

database platforms Cloud Architecture: Experience with Azure data services (Azure Data Factory, Azure Synapse, Azure Data Lake) Data Governance: Understanding of data quality, data lineage, and metadata management principles. ETL/ELT Processes: Experience designing and implementing data integration workflows. Business Intelligence: Knowledge of reporting and analytics platforms (Power BI, SSRS, or similar) Data Warehousing: Experience with dimensional modelling and More ❯