Proven knowledge of physical and logical data modelling in a data warehouse environment including the successful creation of conformed dimensional models from a range of legacy source systems alongside modern SaaS/Cloud business applications
Experience within a similar role within insurance (ideally health insurance) or similar complex and regulated industry, and able to demonstrate a sound working business knowledge of its operation.
Experienced at capturing technical and business metadata including being able to elicit and create sound definitions for entities and attribute.
Practiced and able to query data from source or raw data and reverse engineer an underlying data model and data definitions.
Experienced in writing scripts for data transformation using SQL, DDL, DML, and Pyspark.
Good knowledge and exposure to software development lifecycles and good engineering practices
Can demonstrate a good working knowledge of data modelling patterns and when to use them.
Technical skills
Entity relationship, dimensional, and NOSQL modelling as appropriate to data warehousing, business intelligence, and analytical approaches using IE or other common notations.
SQL, DDL, DML, and Pyspark scripting
ERWIN, and Visio data modelling/UML tool
Ideally, Azure Data Factory, Azure Dev Ops, and Databricks
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Data EngineerEmployement Type: Full time