Constructing data models and structures that will allow both strong data scientific analyses and end-user self-service opportunities Construction, maintenance and optimization of various, multi-technological pipelines executing ETL/ELT processes for all use cases Regular use of cloud technologies such as Microsoft Azure and Synapse Pipelines. Light-touch support of machine learning pipeline construction Management, measurement and delivery of data availability and data observability metrics Experience working with Parquet files BI Reporting experience with Power BI Technology research and awareness to identify new opportunities to improve our pipelines Requirements Essential requirements: Fanatical desire for personal development and personal leadership Strong interpersonal and mentorship skills Outstanding organisation and documentation capability Excellent SQL scripting skills Strong desire to use measurement and metrics to manage and optimise processes Data engineering experience within Python and/or Spark
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