Responsibilities

• Address and resolve data issues and alerts for maintained tables.
• Monitor database health and resource utilization to prevent outages, including NS Quota and Disk Quota.
• Develop new data flow or ETL pipelines to access data from diverse sources.
• Collaborate with stakeholders to understand business and product requirements, and adapt or build systems accordingly.
• Implement best practices and standards for data modeling to ensure the consistency and maintainability of data structures.
  
  

Requirements

• Skill Set: Strong SQL Experience, Spark, PySpark, and Python.
• Good To Have: Hive and Hadoop.
• Experience in Big Data distributed ecosystems: Hadoop, Hive.
• Excellent knowledge of HQL/PrestoQL: Optimisations, complex aggregations, performance tuning.
• Experience building data processing frameworks and big data pipelines.
• Solid understanding of DWH architecture, ELT/ETL processes, and data structures.
• Basic Understanding of Python: ETL.
  
  

This job was posted by Shakti Mishra from Nineleaps.