Senior Engineer, Data Engineering

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Skills you'll use

What you'll do

• Design, develop, and maintain high-performance  ETL/ELT pipelines  using  PySpark  and  Spark SQL  using cloud-native components in  Databricks
• Build and orchestrate data workflows in  AZURE .
• Implement hybrid data integration between on-premise databases and Azure Databricks using tools such as ADF, HVR/Fivetran, and secure network configurations.
• Enhance/optimize Spark jobs for performance, scalability, and cost efficiency.
• Implement and enforce best practices for data quality, governance, and documentation.
• Collaborate with data analysts, data scientists, and business users to define and refine data requirements.
• Support CI/CD processes and automation tools and version control systems like Git.
• Perform root cause analysis, troubleshoot issues, and ensure the reliability of data pipelines.

Who can apply

• Bachelor's degree in Computer Science, Engineering, or related field.
• 4+ years of hands-on experience  in data engineering.
• Proficiency in  PySpark, Spark SQL , and distributed processing.
• Strong knowledge of  Azure  cloud services including ADF, Databricks, and ADLS.
• Experience with SQL, data modeling, and performance tuning.
• Familiarity with Git, CI/CD pipelines, and agile practices.
• Experience with orchestration tools such as Airflow or ADF pipelines.
• Expertise in Databricks, Delta Lake, Unity Catalog and Azure Data Services

About Sandisk

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