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Role is a common data-engineering lead in a metro location with generalist Azure/Databricks requirements, creating medium competition.
Skills are transferable across industries but Azure/Databricks and finance-domain operational controls create moderate domain bias.
Mandatory Azure Databricks/ADF/lakehouse migration and team leadership increase technical gating and make shortlisting strict.
Lead and deliver data engineering projects using Azure services, including Azure Data Factory, Databricks, Data Lake Gen2, and Azure SQL.
Manage and guide a team of data engineers to design and implement data ingestion, transformation pipelines, and Lakehouse/Datawarehouse solutions on Azure cloud.
Drive migration of on-premise data warehouses to Azure cloud and ensure performance tuning, capacity planning, and secure operations aligned with architectural standards.
Experience leading a team of data engineers and managing data engineering projects in Azure environments.
Technical expertise in Azure Data Factory, Databricks, Azure Data Lake Gen2, Azure SQL, and modern data platform architectures.
Proven experience migrating on-premise data warehouses to Azure cloud and implementing Lakehouse/Datawarehouse solutions.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in operating within secured Azure environments utilizing Azure KeyVaults, Service Principals, and Managed Identities.
Skilled in stakeholder management, process adherence, planning, and documentation across project lifecycle activities such as requirement analysis, testing, and release.
Demonstrated ability to collaborate with offshore and onsite teams and engage directly with business stakeholders for requirement gathering and query resolution.