"Databricks Developer"

Core Responsibilities (Data Engineer / Developer)

• Data Pipeline Development: Design, build, and maintain scalable ETL/ELT processes using Databricks and Spark.

• Spark Optimization: Tune and optimize Spark jobs and data transformations for performance.

• Lakehouse Architecture: Implement data reliability, governance, and security using Delta Lake and Unity Catalog.

• Workflow Orchestration: Automate data workflows using Databricks Workflows or tools such as Airflow.

• Collaboration: Work with analysts and business stakeholders.

Key Skills & Technologies

• Languages: PySpark, SQL.

• Databricks Features: Delta Lake, Structured Streaming, Delta Live Tables (DLT).

• Cloud Platforms: AWS, Azure, or GCP.

• DevOps: Git, Terraform, CI/CD practices.

• Tools: Databricks Notebooks, Databricks Repos.