Azure Data Engineer

Qualification:

• Databricks Engineers with 2-3 years of hand-on experience in Pyspark, Cloud Platform and SQL. 
• Proven experience in implementing data solutions on the Databricks platform withhands on experience in setting up Databricks cluster, working in Databricks modules,data pipelines for ingestingand transforming data from various sources into Databricks. 
• Spark-based ETL workflows and data pipelines for data preparation and transformation within Databricks. 

 Responsibilities:

• Bachelors or Masters degree with 4-6 years of professional experience. 
• Proven experience in implementing data solutions on the Databricks platform. 
• Develop, optimize, and maintain Spark-based ETL workflows and data pipelines for data preparation and transformation within Databricks. 
• Knowledge of Performance Optimization, Monitoring and Automation would be a plus. 
• Understanding of data governance, compliance, and security best practices. 
• Strong Proficiency in Pyspark, Databricks Notebooks, SQL, Python, Scala, or Java. 

Key Skills:

• Data warehouse.
• ETL.
• Machine learning.
• Data modeling.
• NoSQL.
• Data pipelines.
• Data security and compliance.
• Data storage and management.
• Problem-solving and critical thinking.