Cloud Data Engineering Specialist

1 week ago


Ajmer, Rajasthan, India beBeeDataEngineer Full time ₹ 30,00,000 - ₹ 40,00,000

Our ideal candidate has expertise in designing and developing scalable data pipelines using Azure Data Factory or Synapse Data Factory for orchestration and ETL processes.

Key Responsibilities:
  • Migrate large-scale SQL workloads to Azure, ensuring high data integrity, minimal downtime, and performance optimization.
  • Develop and manage end-to-end data pipelines utilizing Azure Data Factory or Synapse Data Factory for advanced data transformation and processing.
  • Build secure and efficient data lakes for structured and unstructured data storage during and post-migration.
  • Leverage Azure Databricks, Synapse Spark Pools, Python, and PySpark for complex data transformation and processing tasks.
  • Design and fine-tune SQL/T-SQL scripts for data extraction, cleansing, transformation, and reporting in Azure SQL Database, SQL Managed Instances, and SQL Server.
Requirements:
  • A minimum of 3 years of experience in data engineering with a focus on SQL workload migration to Azure.
  • In-depth knowledge of Azure Data Factory / Synapse Data Factory, Azure Data Lake, Azure Databricks / Synapse Spark Pools, Python, and PySpark.
  • A proven track record of delivering successful data migration projects (on-prem to Azure, or cloud-to-cloud).
What We're Looking For:
  • An innovative problem-solver who can lead complex data engineering projects.
  • A team player who collaborates effectively with cross-functional teams.
  • A self-motivated individual who stays up-to-date with industry trends and best practices.
Benefits:
  • A competitive salary and benefits package.
  • Ongoing training and professional development opportunities.
  • A dynamic and supportive work environment.
About the Role:
  • This is a full-time position requiring a commitment to excellence and customer satisfaction.
  • The ideal candidate will be passionate about delivering high-quality results and meeting deadlines.


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