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Azure Data Engineer

RIT Solutions

Senior Azure Data Analyst

A senior Azure Data Analyst with extensive experience working with the Azure Data suite listed below. The client would like to see certifications.

Candidates must have recent capital markets/trading and/or hedge fund experience and excellent communication skills. Hot & moving fast!

Candidate must have's on a resume and for submittal:

  • How many years working with: Azure Data Analyst
  • How many years working with: Azure Data Factory (ADF)
  • How many years working with: Azure Databricks (highlighted expertise)
  • How many years working with: Logic Apps
  • How many years working with: Capital Markets/Hedge Funds
  • Technical skills:
    • Programming & tools: 10+ years of experience in SQL, Python..Net is a plus.
    • 5+ years of experience in Azure cloud services, including:
      • Azure SQL Server
      • Azure Data Factory (ADF)
      • Azure Databricks (highlighted expertise)
      • Azure Data Lake Storage (ADLS)
      • Azure Key Vault
      • Azure Functions
      • Logic Apps
    • 5+ years of experience in GIT and deploying code using CI/CD pipelines.
  • Certifications (preferred):
    • Microsoft Certified: Azure Data Engineer Associate
    • Databricks Certified Data Engineer Associate or Professional

Responsibilities:

  1. Data Pipeline Development:
  • Create and manage scalable data pipelines to collect, process, and store large volumes of data from various sources.
  • Data Integration:
  • Integrate data from multiple sources, ensuring consistency, quality, and reliability.
  • Database Management:
  • Design, implement, and optimize database schemas and structures to support data storage and retrieval.
  • ETL Processes:
  • Develop and maintain ETL (Extract, Transform, Load) processes to ensure accurate and efficient data movement between systems.
  • Data Warehousing:
  • Build and maintain data warehouses to support business intelligence and analytics needs.
  • Performance Optimization:
  • Optimize data processing and storage performance for efficient resource utilization and quick data retrieval.
  • Documentation:
  • Create and maintain comprehensive documentation for data pipelines, ETL processes, and database schemas.
  • Monitoring and Troubleshooting:
  • Monitor data pipelines and systems for performance and reliability, troubleshooting and resolving issues as they arise.
  • Technology Evaluation:
Vacancy posted 4 days ago
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