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Common senior data-engineer title with Azure focus and hybrid work but modest employer brand yields medium competition.
Core data engineering skills transfer across industries, but Azure specialization and domain preference raise sensitivity to medium.
Mandatory 6–8 years plus required Azure Data Factory, ADLS, MySQL, SQL skills increases shortlisting strictness.
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Design, develop, and maintain data ingestion, transformation, and integration pipelines using Azure Data Factory.
Manage MySQL database operations including query optimization, stored procedures, indexing, and performance tuning.
Develop and maintain data lakes and data warehouses on Azure ensuring data quality, integrity, and governance.
6-8 years of experience in data engineering or related roles with cloud-based architecture focus.
Strong hands-on expertise in Azure Data Factory, Azure Data Lake Storage (ADLS Gen2), MySQL, SQL & PLSQL.
Bachelor’s degree in mathematics, statistics, economics, engineering, or related analytical discipline.
Work Experience Required: 6-8 years specifically in data engineering.
Experienced with version control (Git) and CI/CD practices in data engineering workflows.
Familiar with modern data architectures including Medallion (Bronze/Silver/Gold) design patterns and data governance frameworks.
Has domain familiarity with supply chain management, logistics, or finance analytics is preferred but not mandatory.