1 to 25 of 61 ETL Jobs in the South West

. Experience with Spark, Databricks, or similar data processing tools. Strong technical proficiency in data modeling, SQL, NoSQL databases, and data warehousing. Hands-on experience with data pipeline development, ETL processes, and big data technologies (e.g., Hadoop, Spark, Kafka). Proficiency in cloud platforms such as AWS, Azure, or Google Cloud and cloud-based data services (e.g., AWS Redshift, Azure More ❯

Spark, Databricks, or similar data processing tools. Stron g technical proficiency in data modelin g , SQL, NoSQL databases, and data warehousing . Hands-on experience with data pipeline development, ETL processes, and big data technolo g ies (e. g ., Hadoop, Spark, Kafka). Proficiency in cloud platforms such as AWS, Azure, or Goo g le Cloud and cloud-based More ❯

and other upstream systems into the DWH. Analyse end-to-end data flows across operational and reporting systems. Document and optimise processes relating to data extraction, transformation, and load (ETL). Translate business requirements into clear, testable functional and non-functional specifications. Produce and maintain data dictionaries, lineage documentation, and reporting logic. Act as the primary liaison between business SMEs 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 ❯

databases like Snowflake or SQL Server o Hands-on experience with Snowflake including data modelling, optimization, and managing cloud-based data warehousing solutions. o Experience with building and maintaining ETL data pipelines using tools Azure Data Factory o Solid experience with Git for source code management and collaboration in a development environment o Experience using CI/CD best practices More ❯

skills, Experience in risk management (Market, Credit, Regulatory). Familiarity with risk measures: VAR, CE/PE, PFE. Success in managing multi-terabyte data warehouses. Skilled in data warehousing, ETL/ELT, and reporting tools. Scripting skills (Python, PowerShell). Knowledge of applications, data governance, and cybersecurity.- Preferred: Experience with data modelling tools like dbt. Knowledge of orchestration tools and More ❯

and can do most of the below - please get in touch. You could be exactly what we need! Ideally, we're looking for Develop and maintain data pipelines and ETL processes to integrate and transform diverse data sources into a unified data model. Design and implement data models and database schemas to store and manage large volumes of structured and More ❯

SSIS, SSAS, SSRS, and PowerBI). Proficiency in languages such as Python and SQL, commonly used in Azure data processing. Use of Azure Data Factory for designing and managing ETL workflows. Experience with Microsoft Azure, including deploying and managing data solutions in Azure. Use of Azure Logic Apps for workflow orchestration. Ideally experience of Integration of data from external sources More ❯

SSIS, SSAS, SSRS, and PowerBI). Proficiency in languages such as Python and SQL, commonly used in Azure data processing. Use of Azure Data Factory for designing and managing ETL workflows. Experience with Microsoft Azure, including deploying and managing data solutions in Azure. Use of Azure Logic Apps for workflow orchestration. Ideally experience of Integration of data from external sources More ❯

their data processes Bring leadership and gravitas to a business-facing role. Senior Data Engineer: Must-Have Experience: Strong SQL skills and experience with SSIS, SSRS, SSAS Data warehousing, ETL processes, best practice data management Azure cloud technologies (Synapse, Databricks, Data Factory, Power BI) Python/PySpark Proven ability to work in hybrid data environments Ability to manage and lead More ❯

that support decision-making. 2+ years using Business Intelligence tools (Power BI essential; Looker is a plus but not required). Strong SQL skills and a solid understanding of ETL processes and data pipelines. Experience working with data platforms (e.g., Snowflake , AWS , Kleene ) is highly desirable. Exposure to or interest in the financial services, or purpose-driven sectors is a More ❯

a positive atmosphere, and championing team spirit Master of Science Degree in software engineering or a related field Proficiency in English spoken and written Nice-to-Haves: Experience with ETL/ELT pipeline design and tools (e.g., Apache Airflow). Familiarity with Change Data Capture (CDC) solutions. Knowledge of database services on other cloud platforms (e.g., Azure SQL Database, Google More ❯

communicator, able to translate complex data concepts to cross-functional teams Bonus points for experience with: DevOps tools like Docker, Kubernetes, CI/CD Big data tools (Spark, Hadoop), ETL workflows, or high-throughput data streams Genomic data formats and tools Cold and hot storage management, ZFS/RAID systems, or tape storage AI/LLM tools to accelerate data More ❯

communicator, able to translate complex data concepts to cross-functional teams Bonus points for experience with: DevOps tools like Docker, Kubernetes, CI/CD Big data tools (Spark, Hadoop), ETL workflows, or high-throughput data streams Genomic data formats and tools Cold and hot storage management, ZFS/RAID systems, or tape storage AI/LLM tools to accelerate data More ❯

. Strong hands on experience with AWS (must be able to code in Python within AWS environments). . Proven experience in API development. . Familiarity with cloud-based ETL pipelines. . Strong problem-solving and system optimisation skills. . Strong communication skills, with the ability to clearly articulate technical concepts and collaborate effectively. . SC Clearance is an essential More ❯

environment. The tech stack includes Microsoft Fabric, Power BI and SQL Server Reporting Services. To be considered, you'll need to have experience with Microsoft SQL Server, Data Integration, ETL Pipelines, Power BI and ideally Azure Synapse or Fabric experience. Ideally, you'll have 2 - 3 years of experience in a similar hands-on engineering role. In return, you'll More ❯

Understanding and experience of geoservers, spatial projections, raster and vector manipulation within python and usage of GDAL Experience with AWS and data management tools, including data lake, data warehouse ETL, SQL based storage and PostgreSQL. Ability to design and implement data pipelines and data-related solutions, ideally within a cloud environment Strong ability to document development including database design, application More ❯

to Bristol. What You'll Be Doing as a Data Engineer: Design and architect modern data solutions that align with business objectives and technical requirements Design and implement advanced ETL/ELT pipelines using Python, SQL, and Apache Airflow Build highly scalable and performant data solutions leveraging cloud platforms and technologies Develop complex data models to handle enterprise-level analytical … Contribute to the development of the Methods Analytics Engineering Practice by participating in our internal community of practice Requirements Experience in SQL Server Integration Services (SSIS) Good experience with ETL - SSIS, SSRS, T-SQL (On-prem/Cloud) Strong proficiency in SQL and Python for handling complex data problems Hands-on experience with Apache Spark (PySpark or Spark SQL) Experience More ❯

processes for various bordereaux (both Risk and Claims) using data ingestion and analysis tools such as Intrali, Quantemplate, or Matillion. The project focuses on the extraction, transformation, and loading (ETL) of data from various sources into data warehouses and data lakes. This is an ideal role for an aspiring Data Architect in the Insurance Industry. Pro operates a hybrid working More ❯

in Big Data Java development. In-depth knowledge of Big Data frameworks, such as Hadoop, Spark, and Kafka, with a strong emphasis on Java development. Proficiency in data modeling, ETL processes, and data warehousing concepts. Experience with data processing languages like Scala, Python, or SQL. Familiarity with containerization technologies (Docker) and orchestration tools (Kubernetes). Strong knowledge of software development More ❯

databases and a broad understand across data, including storage, access and governance. You will probably have experience across the following: SQL database systems Optimising SQL queries Data warehousing & pipelines ETL Data security Python Azure and related tools such as PowerBI, Fabric, Data Lake, Data Factory An interest in AI/machine learning would also be beneficial. The company operate a More ❯

databases and a broad understand across data, including storage, access and governance. You will probably have experience across the following: SQL database systems Optimising SQL queries Data warehousing & pipelines ETL Data security Python Azure and related tools such as PowerBI, Fabric, Data Lake, Data Factory An interest in AI/machine learning would also be beneficial. The company operate a More ❯

databases and a broad understand across data, including storage, access and governance. You will probably have experience across the following: SQL database systems Optimising SQL queries Data warehousing & pipelines ETL Data security Python Azure and related tools such as PowerBI, Fabric, Data Lake, Data Factory An interest in AI/machine learning would also be beneficial. The company operate a More ❯

Cloud Platform for Big Data projects, including BigQuery, DataFlow (Apache Beam), Cloud Run, Cloud Functions, Cloud Workflows, and Cloud Composer. Strong SQL development skills. Proven expertise in data modeling, ETL development, and data warehousing. Knowledge of data management fundamentals and storage principles. Familiarity with statistical models or data mining algorithms and their application to business problems. What's in it More ❯

Azure (preferred), AWS, Google Cloud), microservices and event-driven architecture Familiarity with enterprise integration patterns and technologies (e.g., APIs, ESB, messaging systems) Understanding of data architecture, including data modelling, ETL processes, and data governance Soft Skills : Excellent communication and interpersonal skills, with the ability to articulate complex technical concepts to diverse audiences Strong problem-solving and analytical skills Leadership and More ❯