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