Suraj Nair

Over the past year, I have been actively involved in migrating legacy workflows from SAS to Databricks using PySpark. This migration modernized the data processing framework, improved scalability, and optimized performance.

Migration of Legacy Workflows

• Analyzed and re-engineered SAS workflows into efficient PySpark scripts.
• Ensured feature parity while optimizing performance in Databricks.
• Conducted rigorous testing to ensure data accuracy and reliability.
  

Development and Maintenance

• Designed robust data pipelines in Databricks to meet the same business requirements as the SAS workflows.
• Automated data ingestion, transformation, and reporting processes for scalability and efficiency.
• Optimized Spark jobs for cost-effectiveness and faster execution.
  

Collaboration and Knowledge Sharing

• Worked with stakeholders to ensure a seamless transition from SAS to Databricks.
• Documented the migration process and trained team members on Databricks workflows.
  

Ongoing Activities

• Maintain and enhance Databricks data pipelines to replicate and extend SAS functionalities.
• Troubleshoot, debug, and improve existing solutions to meet evolving needs.
• Continuously explore advanced Databricks and PySpark features to add value to the framework.