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Strong brand and metro location increase applicant density despite senior, Azure data engineering specialization.
Azure data engineering skills transfer well, but financial services security and domain context moderately increase specificity.
Multiple mandatory Azure/Databricks skills and enterprise security plus leadership requirements make screening stringent.
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Lead data engineering projects using Azure services like Data Factory, Databricks, Data Lake Gen 2, and SQL to build and operationalize business data solutions.
Lead and provide technical guidance to a team of data engineers ensuring architecture alignment and delivery.
Engage in capacity planning, performance tuning, and migration of on-premise data warehouses to Azure cloud platforms, while managing stakeholder interactions and process documentation.
Experience required in leading data engineering teams and implementing solutions on Azure cloud services.
Proven skills in Azure Data Factory, Databricks, Data Lake Gen 2, and Azure SQL for data ingestion and transformation.
Experience migrating on-premise data warehouses to Azure and working with secured Azure environments using KeyVaults, Service Principals, and Managed Identities.
Work Experience Required: Not explicitly mentioned in the JD.
Demonstrated ability to lead and mentor data engineering teams within cloud-based environments.
Experienced in modern data platform architecture, specifically Lakehouse/Datawarehouse implementations on Azure.
Skilled in collaborating with offshore teams and engaging with business stakeholders for requirement gathering and issue resolution.