Description

Key Responsibilities

 

  • Build and enhance solutions using Databricks Workflows, Delta Lake, Unity Catalog, and Genie.
  • Implement data quality checks leveraging frameworks such as DQX.
  • Design and orchestrate workflows using Airflow or Databricks.
  • Develop high‑quality code using PySpark, Spark SQL, Python, and SQL.
  • Apply performance tuning and cost optimization best practices across pipelines.
  • Leverage Genie to drive automation and productivity use cases.
  • Enforce governance and security policies through Unity Catalog and monitoring practices.
  • Troubleshoot and resolve issues across data pipelines to maintain high reliability.

     

Required Experience & Skills

 

  • 5–8 years of experience in data engineering or Databricks‑focused development.
  • Strong hands‑on expertise with Databricks Workflows, Delta Lake, Unity Catalog, and Genie.
  • Working knowledge of data quality frameworks, ideally DQX.
  • Experience with workflow orchestration using Airflow or Databricks-native tools.
  • Proficiency in PySpark, Spark SQL, Python, and SQL with strong debugging and optimization skills.
  • Strong problem‑solving and communication abilities with solid stakeholder engagement.
  • Proven ability in pipeline performance tuning and cost optimization

Education

Bachelor's degree