Staff Engineer, Data Engineering

About the role

Data Engineering team at SanDisk builds scalable Azure-based data pipelines to power analytics and AI initiatives. The Staff Engineer designs, develops, and optimizes high‑performance ETL/ELT workflows using PySpark, Spark SQL, and Databricks, and integrates on‑premise sources via ADF, HVR or Fivetran. Bangalore, on-site, full‑time role collaborating with analysts, scientists, and business users to ensure reliable, cost‑effective data solutions.

What you’ll do

• Design, develop, and maintain high‑performance ETL/ELT pipelines using PySpark and Spark SQL
• Build and orchestrate data workflows in Azure Databricks and ADF
• Implement hybrid data integration between on‑premise databases and Azure
• Optimize Spark jobs for performance, scalability, and cost efficiency
• Enforce data quality, governance, and documentation standards
• Collaborate with analysts, data scientists, and business users on requirements
• Support CI/CD processes, automation, and version control
• Perform root cause analysis and troubleshoot pipeline issues

What you’ll bring

• 6+ years data engineering experience
• Proficiency with PySpark and Spark SQL
• Strong knowledge of Azure services (ADF, Databricks, ADLS)
• Experience building ETL/ELT pipelines in cloud environments
• SQL data modeling and performance tuning
• Familiarity with CI/CD pipelines and Git
• Experience with data integration tools (HVR, Fivetran)
• Knowledge of streaming platforms like Kafka

Skills

Education

Bachelor's degree in Computer Science, Engineering, or related field