Databricks Engineer (Data Engineer)

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)
• Strong communication skills with client-facing / consulting experience

Databricks certifications preferred (strong indicator of hands-on expertise)