Clear concept of dimensional data modelling(Logical), SCDs, Normalisation and denormalizations.
Thoroughly translating the logical models to physical and data flows per the business requirements. Update and optimise the local and metadata models. Could you evaluate the implemented data system for the variances, discrepancies and efficiencies? Troubleshoot and optimise the existing data flows, models and processing jobs by modularising. Explore ways to enhance the data quality and reliability. Strong in writing UDF Previous knowledge of implementing the DQ framework on Spark would be an added advantage. Good in writing programming using Python/Scala/PySpark is a must. Strong knowledge of spark framework.

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Big Data Engineer