Databricks Engineer

The Databricks Engineer / Developer must demonstrate strong hands-on experience with the following core capabilities:

• Proficiency in SQL, YAML, and Databricks Notebooks for data engineering, analytics, and automation

• Deep understanding and practical application of Medallion Architecture (Bronze, Silver, Gold patterns)

• Experience designing, managing, and optimizing Delta Lake tables

• Strong knowledge of Unity Catalog, including data governance, permissions, lineage, and security best practices

• Hands-on experience building and maintaining AI/BI Dashboards and Reports within Databricks

• Experience configuring and enabling Databricks Genie Rooms

• Practical experience with Natural Language to SQL capabilities and semantic modeling to support business users

• Strong proficiency in Python for data engineering, analytics, and AI workloads

3.2 Version Control, CI/CD, and Environment Management

The Engineer must have demonstrated experience with modern DevOps practices in Databricks environments, including:

• Implementing and managing Databricks Asset Bundles using GitHub

• Applying source control best practices for notebooks, jobs, and configuration

• Promoting and managing solutions across development, UAT, and production environments

• Supporting CI/CD pipelines for Databricks workloads, ensuring repeatability and governance · Experience with Databricks Agents / Agent Bricks

• Designing and implementing agentic workflows for AI-driven automation and decision-making

• Familiarity with retrieval-augmented generation (RAG) or AI orchestration patterns within Databricks