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 - Exposure to CI/CD pipelines (Azure DevOps, GitHub Actions) for data workflows - Experience with infrastructure-as-code tools (Terraform or similar) is an asset - Familiarity with orchestration tools (Airflow, dbt, or ADF pipelines) - Solid communication skills with client-facing / consulting experience - Databricks certifications preferred (strong indicator of hands-on expertise)