A technology focussed individual, data engineers will need to design, configure, develop and deploy data transformations.
Develop ETL pipelines. The data transformations will be developed in Azure Databricks using Python and on Azure SQL using T-SQL and deployed using ARM templates
Combine and curate data in a central data lake
Serve data for application and analytics through a variety of technologies such as SQL, Server Synapse, CosmosDB and TSI
Build transformation pipelines into dimensions and facts and therefore a strong knowledge of standard BI concepts is mandatory
Build stream pipelines leverage IoT Hub, Event Hub, Databricks streaming and other Azure stream technologies
Work in a fluid environment with changing requirements whilst maintaining absolute attention to detail.
Data stream patterns and technology
Data engineering design patterns
Bachelor Degree in Computer Science, Software Engineering or Engineering
Applies to /wiki/spaces/DAGDG/pages/1473251810 and any products that handles large scale data such as images.
Strong experience of building large scale file shipping and pipelines, ideally using Azure services such as AzCopy and Azure Data Lake.
Experience of managing unstructured file meta-data, conversions, standardisation and related workflows.
Experience of building analysis jobs that scale on technologies such as Databricks or Azure Batch.