Minimum 8 years of data engineering experience with at least 5 years hands-on in Pyspark.
Strong knowledge of Azure Data Bricks, Data Lake, Delta Lake, and related Azure services.
Proficiency in SQL, Python or Scala, and understanding of DWH concepts.
Experience with big data frameworks like Hive and Spark, and familiarity with DevOps and Agile methodologies.
Requirements:
Develop and maintain data pipelines using Pyspark and Databricks.
Coordinate with business stakeholders to understand data requirements.
Work with big data technologies and Azure cloud services to support data solutions.
Implement best practices for data transformation and storage.
Job description
Job Description :
Data Engineer with Pyspark, Databricks skillset
8+ years of experience Data Engineering with min 5+ years hands on experience in Pyspark for data transformations.
Sound Knowledge on Azure Data Bricks, Azure Data Lake. Delta Lake, Azure SQL and Azure blob storage, Azure logic apps, Azure Functions and Azure Synapse, Azure Purview.
Extensive knowledge on big data concepts like Hive, and spark framework.
Should be able to write complex SQL queries.
Sound understanding of DWH concepts.
Strong handson experience on Python or Scala.
Hands on experience on SSMS tool related concepts such as Index, store procedure and triggers.
Hands on experience on Azure Data Factory.
Should be able to coordinate independently with business stake holders and understand the business requirements
Knowledge on DevOps and Agile methodologiesbased projects.
Knowledge of version control tool such as GitBitbucket.
Should have basic understanding on Batch Account configuration, various control and monitoring options
