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

7 years - 9 years. in

Azure Databricks technologies.

Experience in

Medallion Architecture

is mandatory. • 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. • Positive communication skills – Oral & Written

📌 Data Engineer (Mumbai)
🏢 Tech Mahindra
📍 Mumbai