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Azure Data Engineer - Data Migration / SQL

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Summary

Builds and maintains Azure-based data solutions in a delivery team: ETL pipelines, data cleaning and validation, warehousing, and Power BI reporting, plus executing data migrations with source-to-target mapping and reconciliation. Core stack: Azure Data Lake, Azure Databricks, Azure SQL Database, SQL, Power BI.


As an Azure Data Engineer within the Delivery department, you will collaborate on designing, building, and maintaining critical data solutions leveraging Azure tools and frameworks. By leveraging your expertise in data engineering and visualization, you will contribute to efficient, secure, and scalable data processing pipelines and insights generation to meet organizational needs.


Key Responsibilities:


  • Design and implement scalable data solutions using Azure Data Lake and Azure Databricks.
  • Develop and maintain data pipelines, ensuring data extraction, transformation, and loading (ETL) processes are efficient and reliable.
  • Perform data cleaning, integration, and validation to ensure data quality and accuracy.
  • Build and manage data warehousing solutions to support analytical capabilities.
  • Create and manage data models and visual representations leveraging Power BI and Azure SQL Database.
  • Implement data governance and ensure compliance with best practices.
  • Collaborate with stakeholders to understand data requirements and deliver analytics solutions that meet business objectives.
  • Develop and execute data migration scripts to migrate data across systems and databases.
  • Perform source-to-target data mapping, migration validation, and data reconciliation to ensure data accuracy and completeness.

Required Skills and Experience:


Mandatory:

  • Proficiency with Azure Data Lake and Azure Databricks.
  • Strong experience in data cleaning and ETL processes.
  • Expertise in data warehousing and data modeling.
  • Proven experience in data migration projects, including migration scripts, source-to-target mapping, and migration validation.
  • Hands-on experience with Power BI and data visualization.
  • Solid knowledge of SQL and Azure SQL Database.
  • Understanding of data governance principles.
  • 4 - 8 years of experience in data engineering or a related field.



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