Qualifications

• Strong hands-on experience with Databricks (PySpark, Delta Lake, notebooks) – core requirement
• Proven ability to build and optimize ETL/ELT data pipelines in a lakehouse environment
• Experience with Azure Data Lake Storage (ADLS Gen2) for scalable data storage
• Hands-on development using Azure Data Factory (ADF) for orchestration and pipelines
• Experience with Azure Functions for serverless data processing
• Solid understanding of lakehouse architecture (Databricks + ADLS integration)
• Strong proficiency in Python and SQL for data transformation and pipeline logic
• Experience with data modeling, partitioning, and performance optimization
• Familiarity with Databricks Unity Catalog (data governance, access control)
• Experience integrating Databricks with Snowflake, APIs, or downstream BI systems