1 to 25 of 207 Remote/Hybrid ETL Jobs in England

reporting, and advanced data use cases. Key Responsibilities Design, develop, and optimize end-to-end data pipelines using Azure services Build and maintain scalable ETL/ELT workflows using Azure Databricks (PySpark/SQL) Develop and manage data warehouses and analytics solutions using Azure Synapse Analytics Ingest data from multiple ...

abilities; comfortable working in a team environment. Essential skills Experience with PowerBI or other BI tools. Knowledge of data warehousing concepts, incremental and batch ETL processes. Familiarity with Agile methodologies and DevOps practices. Experience with Azure cloud services, particularly in data management and analytics. Familiarity with Alteryx for data processing ...

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 Lake, Databricks, and related technologies. Implement and support Microsoft Fabric solutions, including dataflows, data warehouses, and real-time analytics features. Develop and maintain ETL/ELT processes to support business reporting, analytics, and machine learning. Optimise data architectures for performance, reliability, and cost efficiency in cloud environments. Collaborate with ...

years in Professional Services, client-facing delivery roles. Deep knowledge of BI and data warehousing concepts. Solid experience with data modelling, data structures, and ETL processes. Excellent communication and stakeholder management skills. Comfortable explaining technical concepts to varied audiences. Agile delivery experience preferred. What Experience/Skills Do I Need ...

with at least one major cloud platform (Azure, AWS or GCP). Exposure to big data technologies such as Spark or Hadoop. Experience with ETL/orchestration tools like Airflow, Talend or Azure Data Factory. Understanding of data warehousing solutions (Snowflake, BigQuery, Redshift or similar). Good understanding of data ...

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 ...

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 ...

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 ...

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 ...

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 ...

data pipelines and lakehouse architectures on Azure, enabling advanced analytics and data-driven decision making across the business. Key Responsibilities Design, develop, and maintain ETL/ELT pipelines using Azure Databricks, PySpark, and Delta Lake. Build and optimise data lakehouse architectures on Azure Data Lake Storage ( ADLS ) . Develop high ...

developing data products such as data warehouses, data models, reports, and business applications. Knowledge of data lakes and cloud data warehousing solutions. Expertise in ETL/ELT development using tools like Azure Data Factory. Ability to write ETL (extract, transform, load) scripts and code to ensure optimal performance. Understanding ...

ensure best-practice delivery Technology & Experience Essential: Strong hands-on experience with the Azure data platform Proven experience delivering API and enterprise system integrations ETL/ELT pipelines, data modelling, and data warehousing Understanding of how data feeds into Power BI and analytics platforms Desirable: GCP exposure (to support migration ...

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 ...

and take ownership of the roadmap for the ongoing development and enhancement of the Data Platform. Design, implement, and oversee scalable data pipelines and ETL/ELT processes within MS Fabric, leveraging expertise in Azure Data Factory, Databricks, and other Azure services. Advocate for engineering best practices and ensure long ...

reliable, performant, and secure. Key Responsibilities Platform Development & Maintenance Design and implement data pipelines using Azure Data Factory , Databricks , and related Azure services. Build ETL/ELT processes to transform raw data into structured, analytics-ready formats. Optimise pipeline performance and ensure high availability of data services. Infrastructure & Architecture Architect ...

reliable, performant, and secure. Key Responsibilities Platform Development & Maintenance Design and implement data pipelines using Azure Data Factory, Databricks, and related Azure services. Build ETL/ELT processes to transform raw data into structured, analytics-ready formats. Optimise pipeline performance and ensure high availability of data services. Infrastructure & Architecture Architect ...

have the opportunity to: Interpret and validate data requirements, analyse large-scale structured datasets, and ensure data accuracy and completeness. Design and implement ETL frameworks to ingest, transform, validate, normalise, and cleanse data - preparing it for analytics, reporting, and secure storage (e.g., Amazon S3, Azure Blob Storage, BigQuery, Snowflake). ...

have the opportunity to: Interpret and validate data requirements, analyse large-scale structured datasets, and ensure data accuracy and completeness. Design and implement ETL frameworks to ingest, transform, validate, normalise, and cleanse data - preparing it for analytics, reporting, and secure storage (e.g., Amazon S3, Azure Blob Storage, BigQuery, Snowflake). ...

have the opportunity to: Interpret and validate data requirements, analyse large-scale structured datasets, and ensure data accuracy and completeness. Design and implement ETL frameworks to ingest, transform, validate, normalise, and cleanse data - preparing it for analytics, reporting, and secure storage (e.g., Amazon S3, Azure Blob Storage, BigQuery, Snowflake). ...

have the opportunity to: Interpret and validate data requirements, analyse large-scale structured datasets, and ensure data accuracy and completeness. Design and implement ETL frameworks to ingest, transform, validate, normalise, and cleanse data - preparing it for analytics, reporting, and secure storage (e.g., Amazon S3, Azure Blob Storage, BigQuery, Snowflake). ...

have the opportunity to: Interpret and validate data requirements, analyse large-scale structured datasets, and ensure data accuracy and completeness. Design and implement ETL frameworks to ingest, transform, validate, normalise, and cleanse data - preparing it for analytics, reporting, and secure storage (e.g., Amazon S3, Azure Blob Storage, BigQuery, Snowflake). ...

best practises, including data security, data quality and data lineage. Other requirements include: Comfortable working in Microsoft Stack (Fabric, Azure, Power BI) Knowledge of ETL processes, semantic layers and tools like DBT Proficiency in Python for data manipulation and automation Ability to challenge assumptions and educate senior staff on data ...

and setting engineering standards. Collaborate with the Data Architect to design and implement data architecture and build plans. Build and maintain scalable data pipelines, ETL/ELT processes, and large-scale data workflows. Optimise data systems for performance, reliability, and scalability. Implement data quality processes and maintain data models, schemas ...