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Popular data engineering role in a Pune metro with recognizable financial-services brand.
Azure Databricks lakehouse skills transferable, but financial-data context adds moderate domain bias.
Requires specific Azure/Databricks lakehouse expertise and leadership, making filters strict.
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Lead and deliver data engineering projects using Azure services such as Azure Data Factory, Databricks, Data Lake Gen 2, and Azure SQL to build operational data solutions.
Provide technical leadership and guidance to a team of data engineers ensuring alignment with architectural principles and best practices.
Engage with business stakeholders for requirement gathering, deliver performance tuning, capacity planning, and manage secure data environments using Azure security features.
Proven experience leading a team of data engineers and delivering Azure-based data engineering projects.
Strong expertise in Azure Data Factory, Databricks, Data Lake Gen 2, Azure SQL and cloud data platform architecture including migration from on-premises to Azure.
Experience in implementing Lakehouse/Datawarehouse modern data platforms and performance tuning of ADF and Databricks pipelines.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in managing and leading offshore development teams in an agile or project lifecycle environment.
Familiar with operating in secured Azure cloud environments using KeyVaults, Service Principals, and Managed Identities.
Skilled in stakeholder management, process adherence, and documentation with ability to communicate effectively for requirement analysis and query resolution.