Description

You will build and enhance data solutions using Databricks Workflows, Delta Lake, Unity Catalog, and Genie, while implementing data quality checks and orchestrating workflows.

This role is on-site.

Responsibilities

• Develop high-quality code using PySpark, Spark SQL, Python, and SQL to build robust data pipelines.
• Implement data quality checks leveraging frameworks such as DQX to ensure data integrity.
• Design and orchestrate workflows using Airflow or Databricks-native tools for reliable execution.
• Apply performance tuning and cost optimization best practices across all data pipelines.
• Enforce governance and security policies through Unity Catalog and proactive monitoring practices.

Required 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.
• Proficiency in PySpark, Spark SQL, Python, and SQL with strong debugging and optimization skills.
• Working knowledge of data quality frameworks, ideally DQX.
• Experience with workflow orchestration using Airflow or Databricks-native tools.
• Proven ability in pipeline performance tuning and cost optimization.

Preferred Skills

• Strong problem-solving and communication abilities with solid stakeholder engagement.

Key Skills

Education

Bachelor's degree