Cloud Data Engineering Lead

13 hours ago

India beBeeDataEngineering Full time ₹ 15,00,000 - ₹ 28,00,000
Cloud Data Engineering Lead Opportunity

We are seeking an experienced Cloud Data Engineering Lead to manage and lead the migration of an on-premises Enterprise Data Warehouse to a modern cloud-based data platform utilizing Azure Cloud data tools and Snowflake. This platform will enable offshore resources to build and develop Reporting, Analytics, and Data Science solutions.

The successful candidate will be responsible for designing, developing, and implementing data platform solutions using Azure Data Factory (ADF), Self-hosted Integration Runtime (SHIR), Logic Apps, Azure Data Lake Storage Gen2 (ADLS Gen2), Blob Storage, Databricks, and Snowflake.

This role involves managing and guiding the development of cloud-native ETLs and data pipelines using modern technologies on Azure Cloud, Databricks, and Snowflake.

Key Responsibilities:

  • Design and implement data platform solutions using Azure Cloud data tools.
  • Manage and guide the development of cloud-native ETLs and data pipelines.
  • Implement and oversee DevOps practices and CI/CD pipelines using Git Actions.
  • Collaborate with cross-functional teams to ensure seamless integration and data flow.
Required Skills and Qualifications

To be successful in this role, you must have:

  • A minimum of 8+ years of experience in a Cloud Data Engineering role.
  • Hands-on experience with Azure Cloud data tools, Databricks, and Snowflake.
  • Strong experience in developing cloud-native ETLs and data pipelines using modern technologies.
  • Proficiency in DevOps and CI/CD practices using Git Actions.
Benefits

This role offers:

  • A challenging opportunity to work on a large-scale cloud migration project.
  • The chance to design and implement innovative data platform solutions.
  • A collaborative and dynamic work environment.
What We're Looking For

We are looking for a highly skilled and experienced Cloud Data Engineering Lead who can:

  • Provide technical leadership and mentorship to the engineering team.
  • Ensure data security and compliance with industry standards.
  • Optimize and troubleshoot data pipelines and workflows.

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