Azure Data Engineer/Azure/Capital Markets/Hedge Fund - Hybrid/Dallas , TX - 1 year+ Job at Gandiva Insights, Texas

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  • Gandiva Insights
  • Texas

Job Description

Senior Data Engineer

Location:- Dallas, TX

Duration:- 12+ Months

Job Description:

Education:

  • Bachelor's or Master's degree in Computer Science, Information Technology, or a related field (Engineering or Math preferred).

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

Soft Skills:

  • Strong analytical and problem-solving skills.
  • Excellent communication and interpersonal skills.
  • Ability to work independently and collaboratively within a team.
  • Attention to detail and a commitment to delivering high-quality work.

Responsibilities:

  1. Data Pipeline Development:
    • Create and manage scalable data pipelines to collect, process, and store large volumes of data from various sources.
  2. Data Integration:
    • Integrate data from multiple sources, ensuring consistency, quality, and reliability.
  3. Database Management:
    • Design, implement, and optimize database schemas and structures to support data storage and retrieval.
  4. ETL Processes:
    • Develop and maintain ETL (Extract, Transform, Load) processes to ensure accurate and efficient data movement between systems.
  5. Data Warehousing:
    • Build and maintain data warehouses to support business intelligence and analytics needs.
  6. Performance Optimization:
    • Optimize data processing and storage performance for efficient resource utilization and quick data retrieval.
  7. Documentation:
    • Create and maintain comprehensive documentation for data pipelines, ETL processes, and database schemas.
  8. Monitoring and Troubleshooting:
    • Monitor data pipelines and systems for performance and reliability, troubleshooting and resolving issues as they arise.
  9. Technology Evaluation:
    • Stay updated with emerging technologies and best practices in data engineering, evaluating and recommending new tools and technologies as appropriate.

Thanks

Chandra Shekhar Kumar

[email protected]

Job Tags

Full time, Part time, Internship, Seasonal work,

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