End-to-end data loading and extraction in data warehousing
How do build a data warehouse from scratch (including data modeling techniques) how do we design table how do we come up with ETL
Data Architecture:
Familiarity with STAR schema and Snowflake
Understanding of Kimball methodology
Experience with different fact and dimension tables
Performance tuning strategies for large datasets
Data storage strategies for large-scale data
Data Modeling:
Experience in data modeling and ELT architecture
Understanding of subject areas created
Tools & Languages:
Qlik Compose (willing to train)
.NET or Python (preferred)
Additional Qualifications
(Nice to Haves)
Compose experience:
Qlik Compose Development
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