Arunkrishna

Combining proficiency in Azure cloud services
A deep understanding of big data technologies such as Apache Spark.
Strong data modeling, ETL processes, and data integration skills are vital for designing and managing efficient data pipelines.
Knowledge of data warehousing, real-time data processing, and database design, particularly with Azure Synapse Analytics, ensures comprehensive data management.
Continuous learning and adaptability to evolving technologies characterize a successful Azure data engineer, ensuring the optimization of data workflows
Additionally, competence in data secur

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Test And Validate:
After running the dbt models, validate that the target tables in Snowflake have been updated correctly. Check for any errors or unexpected behavior in the incremental loading process.

Schedule And Automate:
Schedule your dbt runs to occur at regular intervals using tools like dbt Cloud, Airflow, or any other scheduling mechanism. This ensures that your data stays up-to-date.

Remember to adapt the SQL queries and the specific configuration options based on you

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