Data Warehouse Specialist

19 hours ago

Mumbai Pune, India beBeeDataEngineer Full time ₹ 18,00,000 - ₹ 25,00,000

Job Opportunity

A highly experienced data engineer with expertise in designing and developing large-scale data analytics and warehouse solutions using Azure Data Factory (ADF) and Azure Data Bricks is required. The ideal candidate will have a proven track record of working in cloud deployments, leveraging modern programming languages, DevOps, SQL and noSQL databases, and test-driven development.

Key Responsibilities

  • Designing large data distribution and integration with service-oriented architecture and data warehouse solutions using Azure Data Bricks with large and multi-format data
  • Translating working solutions into implementable working packages using the Azure platform
  • Working with Azure storage Gen2 and having hands-on experience with Azure stack (minimum 5 years)
  • Proficient coding experience using Spark (Scala/Python), T-SQL, and understanding services related to Azure Analytics, Azure SQL, Azure function app, and logic app
  • Knowledge in Kafka streaming and Azure Infrastructure, with a good understanding of full-stack concepts (backend, frontend, network, OS, middleware, etc)

Requirements

  • High proficiency and 8-10 years of experience in designing/developing data analytics and data warehouse solutions
  • Experience in designing large data distribution, integration with service-oriented architecture, and data warehouse solutions using Azure Data Bricks
  • Ability to translate working solutions into implementable working packages using the Azure platform
  • Good understanding of Azure storage Gen2 and hands-on experience with Azure stack (minimum 5 years)
  • Proficient coding experience using Spark (Scala/Python), T-SQL
  • Understanding around the services related to Azure Analytics, Azure SQL, Azure function app, logic app
  • Good to have knowledge in Kafka streaming and Azure Infrastructure
  • A proven track record of work experience in cloud deployments (MS Azure preferred) in an agile SDLC environment

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