DE&A - Core - Cloud Data Engineering - Databricks

Core data engineering skills:

• Deep understanding of Databricks Lakehouse architecture (Unity Catalog, Delta Lake, Workflows, clusters) - batch and streaming.
• Strong experience with Databricks Notebooks (PySpark/SQL), job orchestration, and production pipeline debugging.
• Expertise in Delta Lake internals: optimization, schema evolution, time travel, Z Ordering, vacuuming.
• Experience troubleshooting:
  • Cluster performance issues
  • Job failures
  • Library/environment conflicts
  • Driver/executor memory issues

 

DevOps skills:

• Strong experience with DevOps pipelines using:
• GitHub Actions / Azure DevOps for CI/CD
• Databricks CLI & REST APIs for automation
• Ability to build automated deployment pipelines for: 
  • Notebooks
  • Workflows
  • UC catalogs, schemas, permissions
  • Cluster policies / job configs

Ability to set up and troubleshoot:

• Databricks job logs
• Cluster metrics
• Audit logs, Unity Catalog events
• Log Analytics dashboards

Responsibilities

Core data engineering skills:

• Deep understanding of Databricks Lakehouse architecture (Unity Catalog, Delta Lake, Workflows, clusters) - batch and streaming.
• Strong experience with Databricks Notebooks (PySpark/SQL), job orchestration, and production pipeline debugging.
• Expertise in Delta Lake internals: optimization, schema evolution, time travel, Z Ordering, vacuuming.
• Experience troubleshooting:
  • Cluster performance issues
  • Job failures
  • Library/environment conflicts
  • Driver/executor memory issues

 

DevOps skills:

• Strong experience with DevOps pipelines using:
• GitHub Actions / Azure DevOps for CI/CD
• Databricks CLI & REST APIs for automation
• Ability to build automated deployment pipelines for: 
  • Notebooks
  • Workflows
  • UC catalogs, schemas, permissions
  • Cluster policies / job configs

Ability to set up and troubleshoot:

• Databricks job logs
• Cluster metrics
• Audit logs, Unity Catalog events
• Log Analytics dashboards

Qualifications

Core data engineering skills:

• Deep understanding of Databricks Lakehouse architecture (Unity Catalog, Delta Lake, Workflows, clusters) - batch and streaming.
• Strong experience with Databricks Notebooks (PySpark/SQL), job orchestration, and production pipeline debugging.
• Expertise in Delta Lake internals: optimization, schema evolution, time travel, Z Ordering, vacuuming.
• Experience troubleshooting:
  • Cluster performance issues
  • Job failures
  • Library/environment conflicts
  • Driver/executor memory issues

 

DevOps skills:

• Strong experience with DevOps pipelines using:
• GitHub Actions / Azure DevOps for CI/CD
• Databricks CLI & REST APIs for automation
• Ability to build automated deployment pipelines for: 
  • Notebooks
  • Workflows
  • UC catalogs, schemas, permissions
  • Cluster policies / job configs

Ability to set up and troubleshoot:

• Databricks job logs
• Cluster metrics
• Audit logs, Unity Catalog events
• Log Analytics dashboards

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