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Azure data bricks with fact & dimension table, Spark SQL, Pyspark, autoloader, unity catalogue & file format JSon - Mandatory
Mandate Skills : Hands on experience in Azure Databricks & Medallion Architecture
• Good understanding of ETL , BI and DW technologies.
• Hands-on experience on Jason or XML files as sources.
• Experience in autoloader for incremental loading and explode options for flattening data
• Experience in loading Delta live tables
• Experience in PySpark or Spark using data frames.
• Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure.
• Work together with data scientists and analysts to understand the needs for data and create effective data workflows.
• Create and maintain data storage solutions including Azure SQL Database, Azure Data Lake, and Azure Blob Storage.
• Utilizing Azure Data Bricks to create and maintain ETL (Extract, Transform, Load) operations.
• Implementing data validation and cleansing procedures will ensure the quality, integrity, and dependability of the data.
• Improve the scalability, efficiency, and cost-effectiveness of data pipelines.
• Monitoring and resolving data pipeline problems to guarantee consistency and availability of the data.
• Good communication skills – Oral & Written
Job ID: 153639191
Skills:
Big Data Technologies, Data Warehousing, Dataproc, Python Programming, Google Cloud Platform GCP, Cloud Composer, SQL PostgreSQL, Cloud Pub Sub, ETL Development Data Pipelines, Large Dataset Processing
Skills:
Azure Data Factory, Pyspark, Sql, Delta Live Tables, Data Bricks
Skills:
Azure Data Factory, Scala, Azure Databricks, Python, Sql, Palantir
Skills:
Data Security, Database Management Systems, data storage solutions, ETL processes, data quality assurance techniques, MicroStrategy Business Intelligence, data pipeline architecture, large-scale data environments
Skills:
Terradata, Pyspark, Kafka, Databricks, Delta Lake, Delta Live Tables, Unity Catalog