Fabric Data Processing Specialist

8 hours ago

Jamnagar, Gujarat, India beBeeDataEngineer Full time ₹ 15,00,000 - ₹ 20,00,000
Job Description

As a skilled Data Engineer with expertise in fabric-based data pipelines and infrastructure, you will play a key role in our team's success. We are seeking an individual who can design, develop, and maintain efficient data processes that enable advanced analytics and reporting.

Our ideal candidate has experience with Azure Data Factory, Databricks, and Azure Synapse Analytics. They are able to work collaboratively with data scientists, analysts, and stakeholders to understand data requirements and deliver actionable insights.

Key Responsibilities:

  • Data Pipeline Development
    • Design and implement data pipelines for seamless data ingestion, transformation, and movement using Azure Data Factory and Databricks.
  • ETL Processes
    • Develop and optimize ETL processes to ensure efficient data flow and transformation.
  • Data Lake Management
    • Develop and maintain Azure Data Lake solutions for efficient storage and retrieval of large datasets.
  • Data Warehousing
    • Work with Azure Synapse Analytics to build scalable data warehousing solutions enabling advanced analytics and reporting.
  • Data Integration
    • Integrate various data sources into MS-Fabric ensuring data consistency, quality, and accessibility across platforms.
  • Performance Optimization
    • Optimize data processing workflows and storage solutions to improve performance and reduce costs.
  • Database Management
    • Manage and optimize databases (SQL and NoSQL) supporting high-performance queries and data storage requirements.
  • Data Quality
    • Implement data quality checks and monitoring to ensure accuracy and consistency of data.
  • Collaboration and Documentation
    • Collaborate with data scientists, analysts, and stakeholders to understand data requirements and deliver actionable insights.
    • Create comprehensive documentation for data processes, pipelines, and infrastructure architecture and best practices.
  • Troubleshooting and Support
    • Identify and resolve issues in data pipelines, data lakes, and warehousing solutions providing timely support and maintenance.

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