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NHS View All Jobs is seeking an early career Data Architect/graduate to support the Data Warehouse team. The role involves ETL/ELT work to move data from clinical and non-clinical systems into a cloud-based data warehouse and to implement specialist ETL knowledge.
You will work with Azure-based architecture, develop best practices, and act as an SME in data management and big data tools while contributing to statutory and corporate data goals.
This is a job share role and an opportunity to spend 12 months with an award winning and internationally accredited data architecture team. Working with an experienced data architect this role would be perfect for an early career data architect or graduate looking to gain paid work experience to enhance their career prospects in this field. This role will support the Data Warehouse team with the operational day to day extraction, transformation and loading of data from various clinical and non clinical systems into a cloud-based data warehouse server and be able to implement and provide specialist knowledge on ETL processes., This is an exciting opening to work on the collecting, storing, processing, and analyzing huge sets of data. The primary focus will be on choosing optimal solutions to use for these purposes, then maintaining, implementing, and monitoring them you will build ETL/ELT best practices in a data environment, featuring data pipelines, working closely with Cloud data architecture (Azure) and be an SME in relation to knowledge of big data tools/platforms, data management tools and necessary infrastructure changes., Manage the preparation and submission of statutory returns Support the delivery and ongoing strategic development of the Data Warehouse. Provide expert advice on aspects of Data Warehousing Work with a variety of highly complex data, systems and software to meet the Trusts statutory and wider corporate objectives Develop and implement extract-transform-load processes with the intention of providing a high-quality service with expert advice to internal teams. This includes analysis, interpretation and transformation of source data from several systems into a data warehouse.