Data Engineer

Working closely with end-users to understand their business and their data requirements.
Ad hoc data analysis and 'data wrangling' using Synapse Analytics and Databricks.
Building dynamic meta-data driven data ingestion patterns using Azure Data Factory and Databricks.
Building and maintaining the Enterprise Data Warehouse (using Data Vault 2.0 methodology).
Building and maintaining business focused data products and data marts.
Building and maintaining Azure Analysis Services databases and cubes.
Building 'infrastructure-as-code' deployment pipelines.
Sharing support and operational duties within the engineering team.
Experience in the following technologies are key to this role:.
Excellent data analysis and exploration using T-SQL.
Strong SQL programming (stored procedures, functions).
Extensive experience with SQL Server and SSIS.
Knowledge and experience of data warehouse modelling methodologies (Data Vault 2.0, Kimball).
Experience in Azure – one or more of the following: Data Factory, Databricks, Synapse Analytics, ADLS Gen2.
Experience in building robust and performant ETL processes.
Build and maintain Analysis Services databases and cubes (both multidimensional and tabular).
Experience in using source control, preferably GIT.
Understanding and experience of deployment pipelines.