Job Summary:
We are looking for an experienced Azure Databricks Developer to contribute to our data modernization and migration initiatives. The role involves understanding existing ETL processes assisting in migration to Azure Databricks and developing scalable data pipelines using PySpark and Delta Lake. The candidate will work closely with data architects and business teams to ensure smooth data transformation and delivery in the Azure ecosystem.
Key Responsibilities:
Analyze and understand existing ETL workflows data mappings and transformation logic.
Develop test and deploy data pipelines using Azure Databricks PySpark and Delta Lake.
Support migration of legacy ETL processes (e.g. SSIS) to Azure Databricks.
Optimize data transformation logic for performance and scalability.
Work with Azure Data Lake Data Factory and Synapse for end-to-end data processing.
Participate in data modeling and data quality validation activities.
Collaborate with senior developers and architects to define technical approaches and standards.
Prepare technical documentation and maintain reusable code components.
Required Skills & Qualifications:
47 years of total experience in data engineering or ETL development.
2 years of hands-on experience with Azure Databricks and PySpark.
Good understanding of ETL concepts data transformation and pipeline orchestration.
Working knowledge of Azure Data Factory Data Lake and Delta Lake.
Strong SQL and debugging skills for data validation and optimization.
Experience with performance tuning and handling large data volumes.
Good communication and problem-solving skills.
Preferred Qualifications:
Experience with SSIS or other ETL tools (for migration understanding).
Basic understanding of data modeling (dimensional star schema).
Familiarity with CI/CD DevOps and Agile environments.
Azure certification (e.g. Azure Data Engineer Associate) is a plus.
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