Enable timely availability of good quality insights to facilitate data driven decision making and self-service analytics.
Design, construct and maintain semantic models such as tabular models/multi-dimensional models to support PSA BUs with scalable analytical models and insights.
Create harmonized insights across all BUs that is aligned with organisation wide definitions.
Recommend ideal data schema to the fellow data engineers for combining data from various functions and business units to enable cross-domain analytics to identify various cost and revenue optimization opportunities.
Work and collaborate with PSA data analytics team at all stages of CRISP-DM Methodology such as business understanding, data understanding, data preparation and data modelling.
Align to PSA data analytics policy, standards and best practices and document as required.

Technical Requirements:

Degree from a recognised university, preferably in Data Analytics or Computer Science domain
.Must have at 5 10 years hands-on experience on semantic data modelling including at least two years using Microsoft azure data tools especially SSMS, SSAS
.Must have knowledge of data warehouse concept (Star, snowflake) methodology and experience in designing data warehouse dimensional modelling
.Must have hands-on experience in SQL, DAX, Azure Synapse Analytics / Datawarehouse, Azure Analysis Services. Having experience on version control tools is a plus
.Good to have: DAX based semantic models from Azure data bricks and/or MS Fabric

Semantic Data Modular - BKC