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Mid-level Azure data engineer role, metro location, reputable employer, and popular skillset increase applicant competition.
Skills are transferable across industries, but finance-focused data security and Azure platform specifics increase fit sensitivity.
Explicit 4–7 years and mandatory Azure/Databricks/PySpark/Azure DevOps skills make filters strict.
Build and operationalize data engineering solutions using Azure services including Data Factory, Databricks, Data Lake Gen 2, SQL, and Power BI support.
Migrate on-premise data warehouses to Azure cloud platforms and implement modern data platform architectures like Lakehouse/Datawarehouse.
Develop and maintain CI/CD pipelines using Azure DevOps and ensure performance tuning and security compliance in Azure environments.
4-7 years of experience in Azure Data Engineering.
Proficiency in Azure Data Factory, Azure Data Lake Storage V2, Azure SQL, Azure Databricks, PySpark, Azure DevOps, and Power BI.
Graduate or Postgraduate degree preferably in Computer Science, Statistics, Mathematics, Data Science, Engineering, or related discipline.
Microsoft Azure certification is preferred but not mandatory.
Experienced in end-to-end Azure cloud data platform development including migration and performance optimization.
Comfortable working with offshore teams and collaborating across business and technical stakeholders.
Demonstrated ability to design, develop, and support data engineering pipelines with security and compliance best practices in highly regulated environments.