Databricks Data Engineer (SSE)

About the job:
We are looking for an experienced Databricks Data Engineer to design, develop, and manage data pipelines using Azure services such as Databricks, Data Factory, and Datalake. The role involves building scalable ETL solutions, collaborating with cross-functional teams, and processing large volumes of data. You will work closely with business and technical teams to deliver robust data models and transformations in support of analytics and reporting needs.

Responsibilities:

• Design and develop ETL pipelines using ADF for data ingestion and transformation.
  
• Collaborate with Azure stack modules like Data Lakes and SQL DW to handle large volumes of data.
  
• Write SQL, Python, and PySpark code to meet data processing and transformation needs.
  
• Understand business requirements and create data flow processes that meet them.
  
• Develop mapping documents and transformation business rules.
  
• Ensure continuous communication with the team and stakeholders regarding project status.
  

Requirements - Must Have:

• 4-7 years of experience in data ingestion, data processing, and analytical pipelines for big data and relational databases.
  
• Extensive hands-on experience with Azure services: Databricks, Data Factory, ADLS, Synapse, and Azure SQL.
  
• Experience in SQL, Python, and PySpark for data transformation and processing.
  
• Strong understanding of DevOps, CI/CD deployments, and Agile methodologies.
  
• Strong communication skills and attention to detail.
  
• Experience in the insurance or financial industry is preferred.